WO2021164633A1 - 权值的发送方法、装置、存储介质及电子装置 - Google Patents

权值的发送方法、装置、存储介质及电子装置 Download PDF

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Publication number
WO2021164633A1
WO2021164633A1 PCT/CN2021/076147 CN2021076147W WO2021164633A1 WO 2021164633 A1 WO2021164633 A1 WO 2021164633A1 CN 2021076147 W CN2021076147 W CN 2021076147W WO 2021164633 A1 WO2021164633 A1 WO 2021164633A1
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Prior art keywords
cell
subnet
broadcast beam
weight
beam weight
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PCT/CN2021/076147
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English (en)
French (fr)
Inventor
马晏铖
谢红军
李家海
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中兴通讯股份有限公司
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Priority to US17/798,392 priority Critical patent/US20230079472A1/en
Priority to EP21757359.1A priority patent/EP4109936A4/en
Publication of WO2021164633A1 publication Critical patent/WO2021164633A1/zh

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/06—Selective distribution of broadcast services, e.g. multimedia broadcast multicast service [MBMS]; Services to user groups; One-way selective calling services
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/10—Monitoring; Testing of transmitters
    • H04B17/15—Performance testing
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/382—Monitoring; Testing of propagation channels for resource allocation, admission control or handover
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H04B7/0456—Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H04B7/0456—Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting
    • H04B7/0482—Adaptive codebooks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
    • H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
    • H04B7/0619—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal using feedback from receiving side
    • H04B7/0621—Feedback content
    • H04B7/0634—Antenna weights or vector/matrix coefficients
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
    • H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
    • H04B7/0619—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal using feedback from receiving side
    • H04B7/0636—Feedback format
    • H04B7/0639—Using selective indices, e.g. of a codebook, e.g. pre-distortion matrix index [PMI] or for beam selection
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0686—Hybrid systems, i.e. switching and simultaneous transmission
    • H04B7/0695—Hybrid systems, i.e. switching and simultaneous transmission using beam selection
    • H04B7/06952—Selecting one or more beams from a plurality of beams, e.g. beam training, management or sweeping
    • H04B7/06958—Multistage beam selection, e.g. beam refinement
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/24—Cell structures
    • H04W16/28—Cell structures using beam steering
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/06—Selective distribution of broadcast services, e.g. multimedia broadcast multicast service [MBMS]; Services to user groups; One-way selective calling services
    • H04W4/08—User group management
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/309—Measuring or estimating channel quality parameters
    • H04B17/318—Received signal strength
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/309—Measuring or estimating channel quality parameters
    • H04B17/336—Signal-to-interference ratio [SIR] or carrier-to-interference ratio [CIR]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/309—Measuring or estimating channel quality parameters
    • H04B17/346—Noise values
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/02—Arrangements for optimising operational condition
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W48/00—Access restriction; Network selection; Access point selection
    • H04W48/08—Access restriction or access information delivery, e.g. discovery data delivery
    • H04W48/12—Access restriction or access information delivery, e.g. discovery data delivery using downlink control channel

Definitions

  • This application relates to the field of communications, for example, to a method, device, storage medium, and electronic device for sending weights.
  • the preset antenna weights can no longer cope with diverse coverage scenarios. In order to cover as many scenarios as possible, it is necessary to increase the number of antenna weight combinations, that is, there are thousands of optional antenna weight combinations for a cell.
  • the complexity of the space is increasing exponentially, and the network planning and optimization methods in related technologies are time-consuming, labor-intensive and inefficient.
  • the embodiments of the present invention provide a weight transmission method, device, storage medium, and electronic device to at least solve the problem of low network optimization efficiency in related technologies.
  • a weight transmission method including:
  • the determined subnet target broadcast beam weight set is sent to the first subnet, where the subnet target broadcast beam weight set is used to instruct the member cells in the first subnet according to the The member target broadcast beam weight corresponding to the member target broadcast beam weight set in the subnet target broadcast beam weight sends the broadcast beam.
  • a weight sending device including:
  • the segmentation module is configured to segment multiple cells to obtain one or more subnets, wherein the subnet includes one or more of the cells, and for any first member cell included in the subnet, the first member cell
  • the degree of overlap between a member cell and a second member cell in the subnet where the first member cell is located is higher than a preset degree threshold, and the second member cell is a neighboring cell of the first member cell ;
  • the determining module is configured to determine, for any first subnet of the one or more subnets, the subnet target broadcast of the first subnet in the preset weight of the member cell according to at least one of the following Beam weight set: the cell coverage of the member cells included in the first subnet, and the inter-cell interference of the member cells included in the first subnet, wherein the target broadcast beam weight set of the subnet includes all Member target broadcast beam weight of each member cell in the first subnet;
  • a sending module configured to send the determined subnet target broadcast beam weight set to the first subnet, wherein the subnet target broadcast beam weight set is used to indicate The member cell of the member cell sends the broadcast beam according to the corresponding member target broadcast beam weight in the subnet target broadcast beam weight set.
  • a computer-readable storage medium in which a computer program is stored, wherein the computer program is configured to execute any of the above-mentioned methods when running.
  • an electronic device including a memory and a processor, the memory is stored with a computer program, and the processor is configured to run the computer program to execute any of the above method.
  • FIG. 1 is a block diagram of the hardware structure of a network management device of a weight transmission method according to an embodiment of the present invention
  • Fig. 2 is a flowchart of a method for sending weights according to an embodiment of the present invention
  • Fig. 3 is a structural block diagram of a weight sending device according to an embodiment of the present invention.
  • Fig. 4 is a flowchart of a network optimization method according to an optional implementation manner of the present application.
  • Fig. 5 is a flowchart of a method for sending weights according to an optional implementation manner of the present application
  • Fig. 6 is a weighted connected graph according to an alternative embodiment of the present application.
  • Fig. 7 is a schematic diagram of a maximum spanning tree according to an alternative embodiment of the present application.
  • Fig. 8 is a schematic diagram of fusing according to an alternative embodiment of the present application.
  • Figure 9 is an algorithm flow chart of the ant colony algorithm.
  • FIG. 1 is a hardware structural block diagram of a network management device of a weight transmission method according to an embodiment of the present invention.
  • the network management device 10 may include one or more (only one is shown in FIG. 1) processor 102 (the processor 102 may include a microprocessor (Microprocessor Control Unit, MCU)) or a field programmable logic device ( Field Programmable Gate Array, FPGA) and other processing devices) and a memory 104 configured to store data.
  • MCU Microprocessor Control Unit
  • FPGA Field Programmable Gate Array
  • the aforementioned network management device may also include a transmission device 106 and an input/output device 108 for communication functions.
  • the structure shown in FIG. 1 is only for illustration, and it does not limit the structure of the above-mentioned network management device.
  • the network management device 10 may also include more or fewer components than those shown in FIG. 1, or have a different configuration from that shown in FIG. 1.
  • the memory 104 may be configured to store computer programs, for example, software programs and modules of application software, such as the computer programs corresponding to the weight transmission method in the embodiment of the present invention.
  • the processor 102 runs the computer programs stored in the memory 104, In this way, multiple functional applications and data processing are executed, that is, the above-mentioned method is realized.
  • the memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory.
  • the memory 104 may include a memory remotely provided with respect to the processor 102, and these remote memories may be connected to the network management apparatus 10 through a network. Examples of the aforementioned networks include the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.
  • the transmission device 106 is configured to receive or transmit data via a network.
  • Examples of the aforementioned network may include a wireless network provided by the communication provider of the network management device 10.
  • the transmission device 106 includes a network adapter (Network Interface Controller, NIC), and the network adapter can be connected to other network devices through a base station so as to communicate with the Internet.
  • the transmission device 106 may be a radio frequency (RF) module, and the transmission device 106 is configured to communicate with the Internet in a wireless manner.
  • RF radio frequency
  • the embodiments of the present application can run on the following network architecture, which includes: a network element (such as a base station) and a network management device, where the network element can perform data collection or data measurement, and the collected or measured data Send to the network management device, the network management device processes the data, and sends the target data obtained after the processing to the network element.
  • the network management device in this embodiment may be a separate device independent of the network element.
  • FIG. 2 is a flowchart of the method for sending weights according to an embodiment of the present invention. As shown in FIG. 2, the flow Including the following steps.
  • Step S202 Divide multiple cells to obtain one or more subnets, where the subnet includes one or more of the cells, and for any one of the first member cells included in the subnet, the first member cell and the first member cell are The degree of inter-cell overlap coverage of a second member cell in a subnet where a member cell is located is higher than a preset degree threshold, and the second member cell is a neighboring cell of the first member cell.
  • Step S204 For any first subnet of the one or more subnets, determine the subnet target broadcast beam weight set of the first subnet from the preset weights of the member cell according to at least one of the following: The cell coverage of the member cells included in the first subnet and the inter-cell interference of the member cells included in the first subnet, wherein the target broadcast beam weight set of the subnet includes each of the first subnets The member target broadcast beam weight of the member cell.
  • Step S206 Send the determined target broadcast beam weight set of the subnet to the first subnet, where the target broadcast beam weight set of the subnet is used to instruct member cells in the first subnet according to the subnet.
  • the target broadcast beam weight of the member in the network target broadcast beam weight set sends the broadcast beam.
  • the low network optimization efficiency in related technologies can be solved To achieve the effect of improving the efficiency of network optimization.
  • the first subnet is determined based on the cell coverage of the member cell included in the first subnet in the preset weight of the member cell.
  • the target broadcast beam weight set of the subnet of the network includes: for each member cell included in the first subnet, the preset power of each member cell is determined according to the reference signal received power of the terminal of each member cell. In the value, the member target broadcast beam weight of each member cell is determined, and the member target broadcast beam weight of each member cell is combined into the subnet target broadcast beam weight set.
  • the cell coverage corresponding to the member target broadcast beam weight of any member cell is higher than the cell coverage corresponding to the preset weights of any member cell except the member target broadcast beam weight. Cell coverage; or,
  • Determining the subnet target broadcast beam weight set of the first subnet from the preset weights of the member cell includes: for each member cell included in the first subnet, according to each member cell The reference signal received power of the terminal determines the member candidate broadcast beam weight of each member cell from the preset weight of each member cell, where the member candidate broadcast beam weight of any member cell corresponds to The cell coverage is higher than the cell coverage corresponding to other preset weights in the preset weights of any one member cell except the weights of the candidate broadcast beams of the member;
  • the member candidate broadcast beam weight of each member cell Determine the target broadcast beam weight set of the subnet, where the inter-cell interference corresponding to the target broadcast beam weight set of the subnet is less than the inter-cell interference corresponding to the other subnet broadcast beam weight sets, and the other subnet broadcast beams
  • the weight value is the subnet broadcast beam weight composed of the member candidate broadcast beam weights of each member cell except the member target broadcast beam weight.
  • the cell coverage can be determined or characterized according to the signal receiving parameters of the cell (for example, reference signal receiving power), and the interference between cells can be determined by signal quality parameters (for example, signal-to-interference plus noise ratio) or Characterization.
  • signal receiving parameters of the cell for example, reference signal receiving power
  • the interference between cells can be determined by signal quality parameters (for example, signal-to-interference plus noise ratio) or Characterization.
  • each subnet may include one or more member cells. Some member cells may not have neighbor cells. For example, a cell can form a subnet by itself and the cell is also There is no neighboring area. For a member cell without a neighboring cell, for example, the target broadcast beam weight of the member cell may be determined only according to the signal receiving parameters of the terminal in the member cell, for example, the above-mentioned method.
  • the subnet target broadcast beam weight For member cells with neighboring cells, when performing network optimization, both cell coverage and inter-cell interference must be considered. Therefore, it can be determined according to the signal receiving parameters of the terminal in the member cell and the signal quality parameter of the member cell.
  • the subnet target broadcast beam weight For member cells with neighboring cells, when performing network optimization, both cell coverage and inter-cell interference must be considered. Therefore, it can be determined according to the signal receiving parameters of the terminal in the member cell and the signal quality parameter of the member cell.
  • the subnet target broadcast beam weight For member cells with neighboring cells, when performing network optimization, both cell coverage and inter-cell interference must be considered. Therefore, it can be determined according to the signal receiving parameters of the terminal in the member cell and the signal quality parameter of the member cell.
  • each member cell is determined from the preset weight of each member cell according to the reference signal received power of the terminal of each member cell
  • the target broadcast beam weights of members include:
  • each member cell traverse each preset weight value of the member cell to obtain the serving cell reference signal received power of the terminal in the member cell corresponding to each preset weight value;
  • the first designated number may be a value such as 10, 100, or 1000.
  • the maximum reference signal received power corresponding to a specified frequency may be any value from 0.3 to 0.6, for example, it may be 0.3, 0.4, 0.5, or 0.6.
  • the preset weight corresponding to the largest maximum reference signal received power is used as the member target broadcast beam weight of the member cell.
  • each member cell is determined from the preset weight of each member cell according to the reference signal received power of the terminal in each member cell
  • Alternative broadcast beam weights for members of including:
  • each member cell traverse each preset weight value of the member cell to obtain the serving cell reference signal received power of the terminal in the member cell corresponding to each preset weight value;
  • the member cell For each preset weight in the member cell, divide the reference signal received power interval formed by the reference signal received power of the serving cell corresponding to the preset weight into a second specified number of equal parts;
  • a member cell since multiple terminals may use a member cell as their serving cell, a member cell will correspond to the serving cell reference signal received power of multiple terminals under a preset weight condition.
  • the interval formed by the minimum value and the maximum value is the reference signal received power interval of the member cell under the preset weight condition.
  • the second specified number can be a value such as 10, 100, or 1000.
  • the reference signal received power of each serving cell corresponding to each preset weight falls within each of the frequencies, and the cumulative frequency distribution is determined as the first 2.
  • the maximum reference signal received power corresponding to the designated frequency in one embodiment, the second designated frequency can be any value from 0.3 to 0.6, such as 0.3, 0.4, 0.5, or 0.6.
  • For each member cell sort the plurality of maximum reference signal received powers corresponding to the member cell according to the numerical value from high to low, and sort one or more of the highest reference signal received powers corresponding to one or more of the highest reference signal received powers.
  • a preset weight is used as the candidate broadcast beam weight of the member cell.
  • the member cell for each member cell, it can be estimated that the member cell is in anticipation based on the member cell's signal parameters obtained under the condition of known weights (for example, the currently effective broadcast beam weights).
  • the signal parameters (measurable or calculable) corresponding to the weights that have been effective can be estimated to correspond to the other weights that are not effective. Signal parameters.
  • the signal parameter of the member cell under the current broadcast beam weight condition may be obtained by direct measurement, or may be obtained by directly processing or filtering some signal parameters obtained by measurement.
  • terminals in a member cell can be understood as a terminal that uses a member cell as a serving cell. Since there can be one or more terminals in a member cell, a member cell corresponds to the measurement data of one or more terminals, for example, corresponding to the reference signal received power measured by one or more terminals.
  • the serving cell of the first terminal corresponding to the second preset weight is referenced
  • the signal received power is the sum of the serving cell reference signal received power of the first terminal corresponding to the first preset weight and the first antenna gain, wherein the first terminal corresponding to the first preset weight
  • the serving cell reference signal received power is measured, and the first antenna gain is determined according to the second preset weight, the first preset weight, and the direction of arrival of the first terminal.
  • the receiving power of the serving cell reference signal of the terminal corresponding to the new preset weight may be estimated based on the receiving power of the serving cell reference signal of the known terminal corresponding to the known preset weight.
  • the receiving power of the serving cell reference signal of the known terminal may be measured by the terminal in the serving cell under the condition that the known preset weight is used to transmit the beam.
  • the "first preset weight” may be a weight that is currently in effect, and the reference signal received power corresponding to the weight that has been in effect can be measured.
  • the “second preset weight value” may be a weight value that has not yet taken effect.
  • the signal to interference plus noise ratio of each terminal in the member cell included in the first subnet under the condition of the member candidate broadcast beam weight is obtained from the member candidate of each member cell.
  • the broadcast beam weights determine the target broadcast beam weight set of the subnet, including:
  • the ant colony algorithm is used to determine the target broadcast beam weight set of the subnet of the first subnet from the member candidate broadcast beam weights of each member cell, wherein the ant colony algorithm
  • the solution of is the target broadcast beam weight set of the subnet.
  • multiple ants are included.
  • the selection result of each ant is a subnet broadcast beam weight set.
  • the subnet broadcast beam weight set is It includes the broadcast beam weights selected by the ants from the candidate broadcast beam weights of each member cell.
  • the determining the target broadcast beam weight set of the subnet of the first subnet from the member candidate broadcast beam weights of each of the member cells by using the ant colony algorithm includes: The probability that only ants select the candidate broadcast beam weight of the member is positively correlated with the expected value of the candidate broadcast beam weight of the member.
  • the expected value of the candidate broadcast beam weight of the member is the
  • the subnet signal of the subnet broadcast beam weight set corresponding to the ant of the member candidate broadcast beam weight is positively correlated with the interference plus noise ratio
  • the subnet signal of the first subnet is the utilization function. It is obtained by processing the signal to interference plus noise ratio of the terminal in the member cell under the condition of the subnet broadcast beam weight set of the first subnet.
  • the expected value of each member's candidate broadcast beam weight is: in the previous iteration process, all the subnets corresponding to the ants that selected the member's candidate broadcast beam weight The average value of the subnet signal to interference plus noise ratio of the broadcast beam weight set.
  • the subnet signal to interference plus noise ratio of the first subnet is to use a function to process the signal to interference plus noise ratio of the terminal in the member cell under the condition of the subnet broadcast beam weight set of the first subnet What you get includes:
  • the first subnet may correspond to multiple signal-to-interference-plus-noise ratios.
  • the interval formed by the minimum and maximum values is the signal and interference plus noise of all the terminals in the first subnet.
  • the third designated number can be a number such as 10, 100, or 1000.
  • the third designated frequency may be any value from 0.3 to 0.6, for example, it may be a value such as 0.3, 0.4, 0.5, or 0.6.
  • the signal to interference plus noise ratio of the terminal in the member cell is: the reference signal received power of the serving cell where the terminal is located, and the neighboring cell reference signal of the neighboring cell of the serving cell measured by the terminal The ratio of the sum of the received power plus the white noise power.
  • the first member candidate broadcast beam weight is the sum of the adjacent cell reference signal received power of the first terminal corresponding to the second member candidate broadcast beam weight and the second antenna gain, where: The neighboring cell reference signal received power of the first terminal corresponding to the second member candidate broadcast beam weight is measured by the first terminal, and the second antenna gain is based on the first member candidate broadcast beam weight Value, the weight of the second member’s candidate broadcast beam and the direction of arrival of the first terminal.
  • the “second member candidate broadcast beam weight” may be a known weight under the condition of a known weight.
  • the received power of the neighboring cell reference signal is estimated, and the known neighboring cell reference signal received power may be measured. If the "second member candidate broadcast beam weight" is a weight that has taken effect, then the neighbor cell reference signal received power corresponding to the "second member candidate broadcast beam weight” can also be measured.
  • the "first member candidate broadcast beam weight” may be an ineffective weight.
  • the using an ant colony algorithm to determine the target broadcast beam weight set of the subnet of the first subnet from the member candidate broadcast beam weights of each member cell includes:
  • an ant colony algorithm to determine the target broadcast beam weight set of the subnet of the first subnet from the member candidate broadcast beam weights of each of the member cells further includes:
  • the subnet broadcast beam weight set corresponding to the largest subnet signal to interference plus noise ratio among the multiple subnet broadcast beam weight sets is used as the target broadcast beam weight of the subnet gather.
  • each ant selects a subnet broadcast beam weight set. Since each subnet broadcast beam weight set corresponds to a subnet signal to interference plus noise ratio, During each iteration, multiple subnet signal to interference plus noise ratios are generated; the larger the subnet signal to interference plus noise ratio, the better the set of broadcast beam weights for the subnet, so you can select all the The subnet broadcast beam weight set corresponding to the largest subnet signal to interference plus noise ratio is used as the subnet target broadcast beam weight set of the subnet.
  • the degree of inter-cell overlap coverage of the first cell and the second cell is an average value of the first overlap coverage and the second overlap coverage, wherein the first overlap coverage is relative to the first cell The overlap coverage of the second cell, where the second overlap coverage is the overlap coverage of the second cell relative to the first cell.
  • the first overlap coverage is: the ratio of the number of measurement report samples meeting the first condition to the number of measurement report samples meeting the second condition in the first cell
  • the first condition includes: the first condition
  • the reference signal received power of the cell is greater than or equal to the first threshold
  • the reference signal received power of the second cell is greater than or equal to the second threshold
  • the reference signal received power of the second cell is the same as the reference signal of the first cell
  • the absolute value of the difference in received power is greater than or equal to a third threshold
  • the second condition includes: the reference signal received power of the first cell is greater than or equal to the first threshold; in this embodiment, the first cell may be a service Cell, the second cell may be a neighboring cell of the serving cell.
  • the second overlap coverage is: the ratio of the number of measurement report samples that meet the third condition to the number of measurement report samples that meet the fourth condition in the second cell
  • the third condition includes: The reference signal received power of the second cell is greater than or equal to the fourth threshold, and the reference signal received power of the first cell is greater than or equal to the fifth threshold, and the reference signal received power of the first cell is the same as the reference signal of the second cell.
  • the absolute value of the difference in signal received power is greater than or equal to the sixth threshold
  • the fourth condition includes: the reference signal received power of the second cell is greater than or equal to the fourth threshold.
  • the second cell may be a serving cell
  • the first cell may be a neighboring cell of the serving cell.
  • the method further includes:
  • the broadcast beam is sent according to the target broadcast beam weight set of the subnet sent to the first subnet.
  • updating the weight of the target broadcast beam of the subnet may be restoring the weight to the initial value.
  • the preset index includes at least one of the following: radio resource control (radio resource control, RRC) connection establishment success rate index, system handover success rate index, wireless drop rate index, spectrum efficiency index, average activation The number of users indicator.
  • radio resource control radio resource control, RRC
  • the method further includes: adjusting the member service beam weight of the corresponding member cell according to the determined member target broadcast beam weight to obtain the member target service beam weight, wherein the member target service beam weight is used to indicate The corresponding target cell sends the service beam according to the member's target service beam weight.
  • the adjusting the member service beam weight of the corresponding member cell according to the determined member target broadcast beam weight to obtain the member target service beam weight includes at least one of the following:
  • the downtilt angle range of the target service beam weight of the member covers the downtilt angle of the broadcast beam weight of the member, and the target service beam weight of the member is obtained.
  • the downtilt angle range of the member target service beam weight covering the downtilt angle of the member target broadcast beam weight may refer to: a member cell may be configured with multiple service beams, and these service beams have their own downtilt angles.
  • the downtilt angles of these different service beams constitute a downtilt angle range, and the downtilt angle of the broadcast beam weight of the member cell needs to be within the downtilt angle range, that is, the downtilt angle range of the service beam weight covers the broadcast beam weight The downward inclination angle.
  • the downtilt angle of the target service beam weight of the member is determined according to the preset number of beams and the preset beam downtilt angle distance.
  • the preset beam downtilt spacing is 2 degrees or 3 degrees, 4 degrees or 5 degrees, etc., and different service beams in the same cell may be continuously distributed at the same downtilt spacing.
  • the method of the foregoing embodiment can be implemented by means of software plus a necessary general hardware platform, or can be implemented by hardware.
  • This application can be embodied in the form of a software product.
  • the computer software product is stored in a computer-readable storage medium (such as ROM/RAM, magnetic disk, optical disk), and includes multiple instructions to enable a terminal device (which can It is a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in the multiple embodiments of the present application.
  • a weight sending device is also provided, which is used to implement the above-mentioned embodiments and implementation manners, and those that have been explained will not be repeated.
  • the term "module” can implement a combination of software and/or hardware with predetermined functions.
  • the devices described in the following embodiments can be implemented by software, implementation by hardware or a combination of software and hardware is also possible and conceived.
  • Fig. 3 is a structural block diagram of a weight sending device according to an embodiment of the present invention. As shown in Fig. 3, the device includes:
  • the dividing module 31 is configured to divide multiple cells to obtain one or more subnets, where the subnet includes one or more of the cells, and for any first member cell included in the subnet, the first member cell
  • the degree of inter-cell overlap coverage of a second member cell in the subnet where the first member cell is located is higher than a preset degree threshold, and the second member cell is a neighboring cell of the first member cell;
  • the determining module 33 is configured to determine, for any first subnet of the one or more subnets, the subnet target broadcast beam right of the first subnet in the preset weight of the member cell according to at least one of the following Value set: the cell coverage of the member cells included in the first subnet, and the inter-cell interference of the member cells included in the first subnet, where the target broadcast beam weight set of the subnet includes those in the first subnet Each member target broadcast beam weight of the member cell;
  • the sending module 35 is configured to send the determined target broadcast beam weight set of the subnet to the first subnet, where the target broadcast beam weight set of the subnet is used to indicate member cells in the first subnet
  • the broadcast beam is sent according to the corresponding member target broadcast beam weight in the subnet target broadcast beam weight set.
  • the target broadcast beam weight of any subnet is determined according to the cell coverage and/or inter-cell interference. Therefore, the low network optimization efficiency in related technologies can be solved To achieve the effect of improving the efficiency of network optimization.
  • the above-mentioned multiple modules can be implemented by software or hardware. For the latter, it can be implemented in the following ways, but not limited to this: the above-mentioned modules are all located in the same processor; or, the above-mentioned multiple modules are respectively in the form of any combination. Located in different processors.
  • the first subnet is determined based on the cell coverage of the member cell included in the first subnet in the preset weight of the member cell.
  • the target broadcast beam weight set of the subnet of the network includes: for each member cell included in the first subnet, the preset power of each member cell is determined according to the reference signal received power of the terminal of each member cell.
  • the member target broadcast beam weight of each member cell is determined in the value, and the member target broadcast beam weight of each member cell is combined into the target broadcast beam weight set of the subnet.
  • the member of any member cell The cell coverage corresponding to the target broadcast beam weight is higher than the cell coverage corresponding to the preset weights of any member cell except the member target broadcast beam weight; or,
  • Determining the subnet target broadcast beam weight set of the first subnet from the preset weights of the member cell includes: for each member cell included in the first subnet, according to each member cell The reference signal received power of the terminal determines the member candidate broadcast beam weight of each member cell from the preset weight of each member cell, where the member candidate broadcast beam weight of any member cell corresponds to The cell coverage is higher than the cell coverage corresponding to other preset weights in the preset weights of any one member cell except the weights of the candidate broadcast beams of the member;
  • the member's candidate broadcast beam weight is obtained from each member cell
  • the target broadcast beam weight set of the subnet is determined in the subnet, where the inter-cell interference corresponding to the target broadcast beam weight set of the subnet is less than the inter-cell interference corresponding to other subnet broadcast beam weight sets, and the other subnet broadcasts
  • the beam weight is a subnet broadcast beam weight composed of the member candidate broadcast beam weights of each member cell except the member target broadcast beam weight.
  • each member cell is determined from the preset weight of each member cell according to the reference signal received power of the terminal of each member cell
  • the target broadcast beam weights of members include:
  • each member cell traverse each preset weight value of the member cell to obtain the serving cell reference signal received power of the terminal in the member cell corresponding to each preset weight value;
  • each preset weight in the member cell it is determined that the reference signal received power of each serving cell corresponding to each preset weight falls within each frequency, and the cumulative frequency distribution is determined as the first A maximum reference signal received power corresponding to a specified frequency;
  • the preset weight corresponding to the largest maximum reference signal received power is used as the member target broadcast beam weight of the member cell.
  • each member cell is determined from the preset weight of each member cell according to the reference signal received power of the terminal in each member cell
  • Alternative broadcast beam weights for members of including:
  • each member cell traverse each preset weight value of the member cell to obtain the serving cell reference signal received power of the terminal in the member cell corresponding to each preset weight value;
  • each preset weight in the member cell it is determined that the reference signal received power of each serving cell corresponding to each preset weight falls within each frequency, and the cumulative frequency distribution is determined as the first 2.
  • the corresponding maximum reference signal received power when the frequency is specified;
  • For each member cell sort the plurality of maximum reference signal received powers corresponding to the member cell according to the numerical value from high to low, and sort one or more of the highest reference signal received powers corresponding to one or more of the highest reference signal received powers.
  • a preset weight is used as the candidate broadcast beam weight of the member cell.
  • the serving cell reference signal of the first terminal corresponding to the second preset weight is the sum of the received power of the serving cell reference signal of the first terminal corresponding to the first preset weight and the first antenna gain, wherein the service of the first terminal corresponding to the first preset weight
  • the cell reference signal received power is measured, and the first antenna gain is determined according to the second preset weight, the first preset weight, and the direction of arrival of the first terminal.
  • the signal to interference plus noise ratio of each terminal in the member cell included in the first subnet under the condition of the member candidate broadcast beam weight is obtained from the member candidate of each member cell.
  • the broadcast beam weights determine the target broadcast beam weight set of the subnet, including:
  • the ant colony algorithm is used to determine the target broadcast beam weight set of the subnet of the first subnet from the member candidate broadcast beam weights of each member cell, wherein the ant colony algorithm
  • the solution of is the target broadcast beam weight set of the subnet.
  • multiple ants are included.
  • the selection result of each ant is a subnet broadcast beam weight set.
  • the subnet broadcast beam weight set is It includes the broadcast beam weights selected by the ants from the candidate broadcast beam weights of each member cell.
  • the using an ant colony algorithm to determine the target broadcast beam weight set of the subnet of the first subnet from the member candidate broadcast beam weights of each member cell includes:
  • the probability that each ant chooses the member’s candidate broadcast beam weight is positively correlated with the expected value of the member’s candidate broadcast beam weight.
  • the expected value of the member’s candidate broadcast beam weight is the The subnet signal of the subnet broadcast beam weight set corresponding to the ant of the candidate broadcast beam weight of the member is positively correlated with the interference plus noise ratio, and the subnet signal of the first subnet is used
  • the function is obtained by processing the signal to interference plus noise ratio of the terminal in the member cell under the condition of the subnet broadcast beam weight set of the first subnet.
  • the expected value of each member's candidate broadcast beam weight is: in the previous iteration process, all the subnets corresponding to the ants that selected the member's candidate broadcast beam weight The average value of the subnet signal to interference plus noise ratio of the broadcast beam weight set.
  • the subnet signal to interference plus noise ratio of the first subnet is to use a function to process the signal to interference plus noise ratio of the terminal in the member cell under the condition of the subnet broadcast beam weight set of the first subnet What you get includes:
  • For the first subnet respectively determine the signal to interference plus noise ratio of the terminal to fall into each equal frequency, determine the maximum signal to interference plus noise ratio corresponding to the third designated frequency when the cumulative frequency distribution is the third designated frequency, and The maximum signal to interference plus noise ratio is used as the subnet signal to interference plus noise ratio corresponding to the subnet broadcast beam weight set.
  • the signal to interference plus noise ratio of the terminal in the member cell is: the reference signal received power of the serving cell where the terminal is located, and the neighboring cell reference signal of the neighboring cell of the serving cell measured by the terminal The ratio of the sum of the received power plus the white noise power.
  • the first member candidate broadcast beam weight is the sum of the neighboring cell reference signal received power of the first terminal corresponding to the second member candidate broadcast beam weight and the second antenna gain, where the The neighboring cell reference signal received power of the first terminal corresponding to the second member candidate broadcast beam weight is measured by the first terminal, and the second antenna gain is based on the first member candidate broadcast beam weight , Determined by the weight of the second member's candidate broadcast beam and the direction of arrival of the first terminal.
  • the using an ant colony algorithm to determine the target broadcast beam weight set of the subnet of the first subnet from the member candidate broadcast beam weights of each of the member cells further includes:
  • an ant colony algorithm to determine the target broadcast beam weight set of the subnet of the first subnet from the member candidate broadcast beam weights of each member cell further includes:
  • the subnet broadcast beam weight set corresponding to the largest subnet signal to interference plus noise ratio among the multiple subnet broadcast beam weight sets is used as the target broadcast beam weight of the subnet gather.
  • the degree of inter-cell overlap coverage of the first cell and the second cell is an average value of the first overlap coverage and the second overlap coverage, wherein the first overlap coverage is relative to the first cell The overlap coverage of the second cell, where the second overlap coverage is the overlap coverage of the second cell relative to the first cell.
  • the first overlap coverage is: the ratio of the number of measurement report samples meeting the first condition to the number of measurement report samples meeting the second condition in the first cell
  • the first condition includes: the first condition
  • the reference signal received power of the cell is greater than or equal to the first threshold
  • the reference signal received power of the second cell is greater than or equal to the second threshold
  • the reference signal received power of the second cell is the same as the reference signal of the first cell
  • the absolute value of the difference in received power is greater than or equal to a third threshold
  • the second condition includes: the reference signal received power of the first cell is greater than or equal to the first threshold; or,
  • the second overlap coverage is: the ratio of the number of measurement report samples meeting the third condition to the number of measurement report samples meeting the fourth condition in the second cell, where the third condition includes: the reference signal of the second cell The received power is greater than or equal to the fourth threshold, and the reference signal received power of the first cell is greater than or equal to the fifth threshold, and the difference between the reference signal received power of the first cell and the reference signal received power of the second cell The absolute value of the value is greater than or equal to the sixth threshold, and the fourth condition includes: the reference signal received power of the second cell is greater than or equal to the fourth threshold.
  • the apparatus further includes:
  • the evaluation module is set to evaluate the target broadcast beam weight set of the subnet according to the preset index, and if the evaluation result does not meet the preset index, roll back the target broadcast beam weight set of the subnet to the initial weight Set; in the case that the evaluation result meets the preset index, the broadcast beam is sent according to the target broadcast beam weight set of the subnet sent to the first subnet.
  • the preset index includes at least one of the following: a radio resource control connection establishment success rate index, a handover success rate index in the system, a wireless drop rate index, a spectrum efficiency index, and an average number of active users index.
  • the device further includes: an adjustment module configured to adjust the member service beam weight of the corresponding member cell according to the determined member target broadcast beam weight to obtain the member target service beam weight, wherein the member target service beam weight The weight is used to indicate that the corresponding target cell sends the service beam according to the member's target service beam weight.
  • an adjustment module configured to adjust the member service beam weight of the corresponding member cell according to the determined member target broadcast beam weight to obtain the member target service beam weight, wherein the member target service beam weight The weight is used to indicate that the corresponding target cell sends the service beam according to the member's target service beam weight.
  • the adjusting the member service beam weight of the corresponding member cell according to the determined member target broadcast beam weight to obtain the member target service beam weight includes at least one of the following: the position of the member target broadcast beam weight The angle is used as the azimuth angle of the member’s service beam weight to obtain the member’s target service beam weight; the member’s target service beam weight’s downtilt range covers the member’s broadcast beam weight’s downtilt angle to obtain the member’s target service beam Weight.
  • the downtilt angle of the target service beam weight of the member is determined according to the preset number of beams and the preset beam downtilt angle distance.
  • this embodiment proposes a method for adaptively adjusting antenna weights in the 4G LTE/5G NR system.
  • This method generates synchronization signals for each cell and PBCH block (synchronization signal and PBCH block, SSB) beam weights and channel state information reference signal (channel state information reference signal, CSI) based on user distribution and measurement report (MR).
  • PBCH block synchronization signal and PBCH block, SSB
  • channel state information reference signal channel state information reference signal
  • CSI channel state information reference signal
  • the SSB beam weight is equivalent to a broadcast beam weight.
  • the CSI-RS beam weight is equivalent to a service beam weight.
  • FIG. 4 is a flowchart of a network optimization method according to an optional embodiment of the application, as shown in FIG. 4. Show, including:
  • Optimized area selection and task configuration are performed on the network management side, and the tasks are delivered to the network elements.
  • the optimization area can be specified by the network optimization personnel, or can be automatically identified by the tool, the task configuration selects the target that needs to be optimized, and the task is activated.
  • the network element performs MR data collection and Angle of Arrival (Direction of Arrival, DOA) data measurement, and reports the data to the network manager.
  • DOA Angle of Arrival
  • the network manager performs subnet segmentation and optimal weight estimation based on the collected data.
  • the network manager issues the new weights to the network element to take effect, and the network element collects key performance indicators (Key Performance Indicator, KPI) and reports it to the network manager.
  • KPI Key Performance Indicator
  • the network manager performs weight evaluation based on the collected KPI information. If the evaluation is passed, the weight is updated to the network element; if the evaluation fails, the weight is issued to the network element.
  • Fig. 5 is a flowchart of a method for sending weights according to an optional implementation manner of the present application, as shown in Fig. 5, including:
  • Data collection such as collecting measurement reports reported by the terminal.
  • Subnet segmentation where, for example, the process of subnet segmentation may be as follows:
  • the subnet segmentation is performed based on the collected MR data.
  • the subnet segmentation operation calculates the overlap coverage of each cell and its neighboring cells based on the MR measurement results, and the overlap coverage reflects the association of the two cells The degree of compactness, the greater the overlap coverage, the closer the relationship is considered.
  • the number of cells per subnet is limited to CellNumThr, which is 50 by default and can be configured.
  • the steps for subnetting are as follows.
  • cell A calculates the overlap coverage method of cell B:
  • RSRPi serving cell's Reference Signal Receiving Power
  • RSRPj neighboring RSRP
  • RSRPi is greater than or equal to "serving cell coverage RSRP threshold ucOverlapSrvThd";
  • RSRPj is greater than or equal to "neighbor cell overlap coverage RSRP threshold ucOverlapNbrThd";
  • abs(RSRPj-RSRPi) is greater than or equal to "neighbor cell overlap coverage RSRP difference threshold ucOverlapNbrDifferThd", where abs() represents an absolute value.
  • B is the serving cell
  • A is the neighboring cell of cell B
  • RSRPi is the serving cell RSRP
  • RSRPj is the neighboring RSRP
  • RSRPi is greater than or equal to "serving cell coverage RSRP threshold ucOverlapSrvThd";
  • RSRPj is greater than or equal to "neighbor cell overlap coverage RSRP threshold ucOverlapNbrThd";
  • abs(RSRPj-RSRPi) is greater than or equal to the "neighbor cell overlap coverage RSRP difference threshold ucOverlapNbrDifferThd", where abs() represents the absolute value;
  • the association relationship between multiple cells can be calculated according to User Equipment (UE) data. If there are 15 cells A to O, then a weighted connectivity graph as shown in FIG. 6 can be constructed.
  • FIG. 6 is a weighted connectivity graph according to an optional embodiment of the present application, and the edge in FIG. 6 is the degree of association between the two cells.
  • the subnet is generated through Prim's algorithm.
  • the maximum spanning tree can be generated by continuously increasing the fuse threshold of the degree of association between different cells in the cell weighted connectivity graph, as follows:
  • the basic principle of the subnet segmentation method is to divide the closely connected cells into a subset.
  • the Prim algorithm in graph theory can be used to obtain the maximum spanning tree.
  • the maximum spanning tree can ensure that all cells are still connected.
  • Primm's algorithm for solving the maximum spanning tree is as follows:
  • Input a weighted connected graph, where the set of vertices is V and the set of edges is E.
  • Output Use sets Vnew and Enew to describe the maximum spanning tree obtained.
  • Fig. 7 is a schematic diagram of a maximum spanning tree according to an alternative embodiment of the present application.
  • the edges whose weights are less than the threshold are blown, for example, the edges whose weight is less than 0.2 are blown to obtain the
  • Fig. 8 is a schematic diagram of fusing according to an alternative embodiment of the present application.
  • the subnet includes a maximum of 7 cells, and each subnet satisfies that the subnet includes a maximum of 9 cells. The maximum number of cells included is configurable).
  • the fuse threshold setting is unreasonable, and the fuse threshold needs to be increased. Since the number of cells in the subnet described in Figure 7 exceeds the preset value (for example, it can be 9), the fuse threshold can be continuously increased so that the number of cells contained in each subnet after division is less than or equal to the number of subnets. The maximum number of cells threshold.
  • CDF cumulative distribution function
  • SINR Noise Ratio
  • This step includes the following steps:
  • Each cell in the subnet uses the maximum RSRP CDF50 as the cost function according to the user's DOA and MR data, and obtains the TOP N optimal weights for each cell through the traversal method.
  • the RSRP CDF50 cost function calculation formula is as follows.
  • the RSRP of the UE in the serving cell under the new weight is calculated based on the RSRP reported by the MR and the antenna gain under the new weight. Assuming that the UEi is reported as RSRPi,k in the MR corresponding to the weight k, and the DOA angle corresponding to the UE is (h,v), then when the new weight j is selected, the calculation method for the UE's RSRPi,j is as follows:
  • RSRPi,j RSRPi,k+AntGainTbl[j][h][v]-AntGainTbl[k][h][v]
  • AntGainTbl is the saved 3D antenna gain table.
  • the estimation method for the UE to measure the RSRP of the neighboring cell is the same, and the DOA information of the UE in multiple neighboring cells is obtained by the neighboring cell assisted measurement.
  • the RSRP value is used as the cost function value.
  • the RSRP CDF50 value of each weight is calculated, and the largest TOP N weights are used as the candidate weights for subsequent SINR CDF50 optimization.
  • SINR CDF50 cost function As the cost function to maximize the cost function, and the joint optimal weights of all cells in the subnet are obtained through the ant colony algorithm.
  • the calculation formula of the SINR CDF50 cost function is shown below.
  • the calculation formula for the RSRP of the serving cell and the RSRP of the neighboring cell is the same as step 1).
  • RSRP needs to be converted to a linear value before calculating the SINR.
  • SINR calculation requires maximum/minimum protection, -20dB ⁇ SINR ⁇ 40dB.
  • the "neighboring cell" in the foregoing UE SINR calculation method refers to all the neighboring cells measured by the terminal in the MR measurement report reported by each terminal.
  • each terminal corresponds to a UE SINR under a weight condition. Since there may be multiple cells in a subnet, each cell corresponds to multiple alternative weights. There may be multiple terminals. Therefore, a subnet can correspond to multiple UE SINRs. Sort the UE SINRs of all terminals in all cells corresponding to a subnet from small to large, and divide the SINR interval into 1000 equal parts. Between SINR cells, count the frequencies that fall into each SINR cell, calculate the maximum SINR value in the corresponding SINR cell when the SINR cumulative distribution is 0.5 as the cost function value, and calculate the joint search weights of all cells through the ant colony algorithm. The cells are all searched from the candidate weights obtained in step 1).
  • Figure 9 is an algorithm flow chart of the ant colony algorithm, as shown in Figure 9, including:
  • Initialization parameters among them, the parameters that need to be initialized include the number of ants m, the pheromone importance factor ⁇ , the heuristic function importance factor ⁇ , the pheromone volatilization factor ⁇ , the pheromone intensity coefficient Q, and the maximum number of iterations Iter_Max.
  • the weight of each cell is one of the selected N candidate weights (that is, the above-mentioned candidate weight).
  • the selection probability of each weight in each cell is determined by the following formula:
  • -P i k represents the probability of ant k choosing weight i
  • - ⁇ i (t) represents the pheromone concentration on the weight i at time t;
  • - ⁇ i (t) is the expected value of the weight, which represents the expected degree of the weight i at time t.
  • the expected value ⁇ i (t) is defined as the value calculated by the cost function of all cells in the weight solution space. Depending on the search purpose, the processing of ⁇ i (t) is slightly different:
  • the selection probability of each weight is calculated based on the weight-pheromone concentration-weight expectation table maintained by each cell.
  • the initial value of the pheromone concentration is ⁇ 0
  • the weight expectation is initialized to ⁇ 0
  • the initial selection of each weight The probability is 1/N (N is the number of alternative weights).
  • Weight w Pheromone concentration ⁇ i (t) Expected weight ⁇ i (t) Probability P W0 ⁇ 0 ⁇ 0 1/N W1 ⁇ 0 ⁇ 0 1/N ... ... ... ... WN-2 ⁇ 0 ⁇ 0 1/N WN-1 ⁇ 0 ⁇ 0 1/N
  • Table 1 is the weight-pheromone concentration-weight expectation table. Each cell needs to maintain Table 1 as the previous one.
  • the weight expectation is The average value of the cost function calculated by all the ants that have selected the weight in the community.
  • the weight selection adopts the probability selection method of Russian roulette. Different color blocks on the roulette wheel represent different weights. The width of the color block represents the selection probability of the corresponding weight. The wider the color block, the higher the selection probability.
  • ⁇ k represents the pheromone concentration released by the k-th ant on the weight. If the ant does not select the weight in this iteration, the pheromone concentration released by the ant is 0; ⁇ represents all the ants at the weight. The sum of the pheromone concentrations released. The more a weight is selected by ants, the greater the pheromone concentration.
  • the pheromone released by ants uses the ant cycle system model.
  • the formula for calculating ⁇ k is as follows:
  • Q is a constant, which represents the pheromone increase intensity coefficient.
  • the value of this parameter determines the convergence speed of the algorithm to a certain extent, and ⁇ is determined by the value function. The larger the ⁇ , the higher the pheromone concentration released by the UE.
  • the azimuth and tilt angles of the optimal SSB beam weights for each cell can be used to adjust the CSI-RS beam weights.
  • the optimal broadcast beam information is used to adjust the service beams simultaneously. Adjusting the broadcast beam and service beam can also avoid the calculation overhead caused by adjusting the service beam separately.
  • the service beam can be set to 4 beams, the horizontal width of the 4 beams is fixed to 50 degrees, and the vertical width is fixed to 6 degrees; the azimuth angle of the service beam is taken from the composite pattern of each SSB (Pattern )'S azimuth angle (Azimuth); the downward tilt angle of the service beam is adjusted according to SSB Beam tilt.
  • the rule table is as follows:
  • the corresponding CSI-RS 4 beam weights are CSI_beam0 azimuth.
  • CSI_beam3 azimuth angle is 20 degrees, downtilt angle is 9 degrees, horizontal wave width is 50 degrees, and vertical wave width is 6 degrees.
  • the weights are spliced according to the subnet ID from small to large, and the weights are combined according to the base station ID and the cell ID in the order of small to large in the subnet.
  • KPI evaluation is performed on each subnet. If the evaluation is passed, the weight is updated; if the evaluation is not passed, the weight is rolled back.
  • KPIs include: basic KPIs and performance KPIs; basic KPIs include: the success rate of RRC connection establishment, the success rate of switching out of the system, and the rate of wireless disconnection. Performance KPIs include: Spectral Efficiency (SE), average number of active users, etc.
  • SE Spectral Efficiency
  • KPI evaluation is evaluated in accordance with the following rules:
  • the cell-level indicator evaluation passes, otherwise the cell-level indicator evaluation fails.
  • the embodiment of the present invention also provides a computer-readable storage medium in which a computer program is stored, wherein the computer program is configured to execute the steps in any of the foregoing method embodiments when running.
  • the aforementioned storage medium may be configured to store a computer program for executing the following steps:
  • S2 For any first subnet of the one or more subnets, determine the subnet target broadcast beam weight set of the first subnet from the preset weights of the member cell according to at least one of the following: the The cell coverage of the member cells included in the first subnet, and the inter-cell interference of the member cells included in the first subnet, wherein the target broadcast beam weight set of the subnet includes each of the first subnets.
  • the member target broadcast beam weight of the member cell For any first subnet of the one or more subnets, determine the subnet target broadcast beam weight set of the first subnet from the preset weights of the member cell according to at least one of the following: the The cell coverage of the member cells included in the first subnet, and the inter-cell interference of the member cells included in the first subnet, wherein the target broadcast beam weight set of the subnet includes each of the first subnets.
  • the member target broadcast beam weight of the member cell The member target broadcast beam weight of the member cell.
  • the low network optimization efficiency in related technologies can be solved To achieve the effect of improving the efficiency of network optimization.
  • the aforementioned storage medium may include: Universal Serial Bus flash disk (USB flash disk), Read-Only Memory (ROM), random access memory ( Random Access Memory, RAM), mobile hard drives, magnetic disks or optical discs and other media that can store computer programs.
  • USB flash disk Universal Serial Bus flash disk
  • ROM Read-Only Memory
  • RAM Random Access Memory
  • mobile hard drives magnetic disks or optical discs and other media that can store computer programs.
  • An embodiment of the present invention also provides an electronic device, including a memory and a processor, the memory stores a computer program, and the processor is configured to run the computer program to execute the steps in any one of the foregoing method embodiments.
  • the aforementioned electronic device may further include a transmission device and an input-output device, wherein the transmission device is connected to the aforementioned processor, and the input-output device is connected to the aforementioned processor.
  • the foregoing processor may be configured to execute the following steps through a computer program:
  • S2 For any first subnet of the one or more subnets, determine the subnet target broadcast beam weight set of the first subnet from the preset weights of the member cell according to at least one of the following: the The cell coverage of the member cells included in the first subnet, and the inter-cell interference of the member cells included in the first subnet, wherein the target broadcast beam weight set of the subnet includes each of the first subnets.
  • the member target broadcast beam weight of the member cell For any first subnet of the one or more subnets, determine the subnet target broadcast beam weight set of the first subnet from the preset weights of the member cell according to at least one of the following: the The cell coverage of the member cells included in the first subnet, and the inter-cell interference of the member cells included in the first subnet, wherein the target broadcast beam weight set of the subnet includes each of the first subnets.
  • the member target broadcast beam weight of the member cell The member target broadcast beam weight of the member cell.
  • the low network optimization efficiency in related technologies can be solved To achieve the effect of improving the efficiency of network optimization.
  • the above-mentioned multiple modules or multiple steps of this application can be implemented by a general computing device. They can be concentrated on a single computing device or distributed on a network composed of multiple computing devices. Optionally, they can be It is implemented by the program code executable by the computing device, so that they can be stored in the storage device to be executed by the computing device, and in some cases, the steps shown or described can be executed in a different order than here, Or they can be made into multiple integrated circuit modules respectively, or multiple modules or steps of them can be made into a single integrated circuit module to achieve. In this way, this application is not limited to any specific combination of hardware and software.

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Abstract

本申请提供了一种权值的发送方法、装置、存储介质及电子装置，权值的发送方法包括：分割多个小区，得到一个或多个子网，对于该一个或多个子网中的任意一个第一子网，根据以下至少之一在成员小区的预设权值中确定该第一子网的子网目标广播波束权值集合：该第一子网所包括的成员小区的小区覆盖、该第一子网所包括的成员小区的小区间干扰；将确定后的该子网目标广播波束权值集合发送至该第一子网。

Description

权值的发送方法、装置、存储介质及电子装置
本申请要求在2020年02月17日提交中国专利局、申请号为202010095918.4的中国专利申请的优先权，该申请的全部内容通过引用结合在本申请中。
技术领域
本申请涉及通信领域，例如涉及一种权值的发送方法、装置、存储介质及电子装置。
背景技术
预设天线权值已无法应对多样化的覆盖场景，为了覆盖尽可能多的场景，需要增加天线权值组合数，即一个小区有上千种可选天线权值组合数，对于第四代移动通信技术长期演进/第五代移动通信技术新空口(the 4th Generation Mobile Communication Technology Long Term Evolution/the 5th Generation Mobile Communication Technology New Radio，4G LTE/5G NR)超密集同频组网，天线权值搜索空间的复杂度呈指数级增长，相关技术中的网规网优手段耗时、耗力且效率低。
发明内容
本发明实施例提供了一种权值的发送方法、装置、存储介质及电子装置，以至少解决相关技术中网优效率较低的问题。
根据本发明的一个实施例，提供了一种权值的发送方法，包括：
分割多个小区，得到一个或多个子网，其中，所述子网包括一个或多个所述小区，对于所述子网所包括的任意一个第一成员小区，所述第一成员小区与所述第一成员小区所在的子网中的第二成员小区的小区间重叠覆盖程度高于预设的程度阈值，所述第二成员小区为所述第一成员小区的邻小区；
对于所述一个或多个子网中的任意一个第一子网，根据以下至少之一在所述成员小区的预设权值中确定所述第一子网的子网目标广播波束权值集合：所述第一子网所包括的成员小区的小区覆盖、所述第一子网所包括的成员小区的小区间干扰，其中，所述子网目标广播波束权值集合包括所述第一子网中的每 一个所述成员小区的成员目标广播波束权值；
将确定后的所述子网目标广播波束权值集合发送至所述第一子网，其中，所述子网目标广播波束权值集合用于指示所述第一子网中的成员小区根据所述子网目标广播波束权值集合中对应的所述成员目标广播波束权值发送广播波束。
根据本发明的另一个实施例，提供了一种权值的发送装置，包括：
分割模块，设置为分割多个小区，得到一个或多个子网，其中，所述子网包括一个或多个所述小区，对于所述子网所包括的任意一个第一成员小区，所述第一成员小区与所述第一成员小区所在的子网中的第二成员小区的小区间重叠覆盖程度高于预设的程度阈值，所述第二成员小区为所述第一成员小区的邻小区；
确定模块，设置为对于所述一个或多个子网中的任意一个第一子网，根据以下至少之一在所述成员小区的预设权值中确定所述第一子网的子网目标广播波束权值集合：所述第一子网所包括的成员小区的小区覆盖、所述第一子网所包括的成员小区的小区间干扰，其中，所述子网目标广播波束权值集合包括所述第一子网中的每一个所述成员小区的成员目标广播波束权值；
发送模块，设置为将确定后的所述子网目标广播波束权值集合发送至所述第一子网，其中，所述子网目标广播波束权值集合用于指示所述第一子网中的成员小区根据所述子网目标广播波束权值集合中对应的所述成员目标广播波束权值发送广播波束。
根据本发明的又一个实施例，还提供了一种计算机可读的存储介质，所述存储介质中存储有计算机程序，其中，所述计算机程序被设置为运行时执行上述任一项方法。
根据本发明的又一个实施例，还提供了一种电子装置，包括存储器和处理器，所述存储器中存储有计算机程序，所述处理器被设置为运行所述计算机程序以执行上述任一项方法。
附图说明
图1是本发明实施例的一种权值的发送方法的网管装置的硬件结构框图；
图2是根据本发明实施例的权值的发送方法的流程图；
图3是根据本发明实施例的权值的发送装置的结构框图；
图4是根据本申请可选实施方式的网优方法的流程图；
图5是根据本申请可选实施方式的权值的发送方法的流程图；
图6是根据本申请可选实施方式的加权连通图；
图7是根据本申请可选实施方式的最大生成树示意图；
图8是根据本申请可选实施方式的熔断示意图；
图9是蚁群算法的算法流程图。
具体实施方式
下文中将参考附图并结合实施例来说明本申请。在不冲突的情况下，本申请中的实施例及实施例中的特征可以相互组合。
本申请的说明书和权利要求书及上述附图中的术语“第一”、“第二”等是用于区别类似的对象，而不必用于描述特定的顺序或先后次序。
实施例1
本申请实施例一所提供的方法实施例可以在网管装置或者类似的运算装置中执行。以运行在网管装置上为例，图1是本发明实施例的一种权值的发送方法的网管装置的硬件结构框图。如图1所示，网管装置10可以包括一个或多个(图1中仅示出一个)处理器102(处理器102可以包括微处理器(Microprocessor Control Unit，MCU)或现场可编程逻辑器件(Field Programmable Gate Array，FPGA)等的处理装置)和设置为存储数据的存储器104，可选地，上述网管装置还可以包括用于通信功能的传输设备106以及输入输出设备108。图1所示的结构仅为示意，其并不对上述网管装置的结构造成限定。例如，网管装置10还可包括比图1中所示更多或者更少的组件，或者具有与图1所示不同的配置。
存储器104可设置为存储计算机程序，例如，应用软件的软件程序以及模块，如本发明实施例中的权值的发送方法对应的计算机程序，处理器102通过 运行存储在存储器104内的计算机程序，从而执行多种功能应用以及数据处理，即实现上述的方法。存储器104可包括高速随机存储器，还可包括非易失性存储器，如一个或者多个磁性存储装置、闪存、或者其他非易失性固态存储器。在一些实例中，存储器104可包括相对于处理器102远程设置的存储器，这些远程存储器可以通过网络连接至网管装置10。上述网络的实例包括互联网、企业内部网、局域网、移动通信网及其组合。
传输设备106设置为经由一个网络接收或者发送数据。上述的网络的实例可包括网管装置10的通信供应商提供的无线网络。在一个实例中，传输设备106包括一个网络适配器(Network Interface Controller，NIC)，网络适配器可通过基站与其他网络设备相连从而可与互联网进行通讯。在一个实例中，传输设备106可以为射频(Radio Frequency，RF)模块，传输设备106设置为通过无线方式与互联网进行通讯。
本申请实施例可以运行于如下所述的网络架构上，该网络架构包括：网元(例如基站)和网管装置，其中，网元可以进行数据收集或者数据测量，并将收集或者测量得到的数据发送给网管装置，网管装置对数据进行处理，并将处理后得到的目标数据下发给网元。本实施例中的网管装置可以是独立于网元的单独的装置。
在本实施例中提供了一种运行于上述网管装置或网络架构的权值的发送方法，图2是根据本发明实施例的权值的发送方法的流程图，如图2所示，该流程包括如下步骤。
步骤S202，分割多个小区，得到一个或多个子网，其中，该子网包括一个或多个该小区，对于该子网所包括的任意一个第一成员小区，该第一成员小区与该第一成员小区所在的子网中的第二成员小区的小区间重叠覆盖程度高于预设的程度阈值，该第二成员小区为该第一成员小区的邻小区。
步骤S204，对于该一个或多个子网中的任意一个第一子网，根据以下至少之一在该成员小区的预设权值中确定该第一子网的子网目标广播波束权值集合：该第一子网所包括的成员小区的小区覆盖、该第一子网所包括的成员小区的小区间干扰，其中，该子网目标广播波束权值集合包括该第一子网中的每一个该成员小区的成员目标广播波束权值。
步骤S206，将确定后的该子网目标广播波束权值集合发送至该第一子网，其中，该子网目标广播波束权值集合用于指示该第一子网中的成员小区根据该子网目标广播波束权值集合中对应的该成员目标广播波束权值发送广播波束。
通过上述步骤，由于将多个小区划分为一个或多个子网，根据小区覆盖和/或小区间干扰确定任意一个子网的目标广播波束权值，因此，可以解决相关技术中网优效率较低的问题，达到提高网优效率的效果。
可选地，该对于该一个或多个子网中的任意一个第一子网，根据该第一子网所包括的成员小区的小区覆盖在该成员小区的预设权值中确定该第一子网的子网目标广播波束权值集合，包括：对于该第一子网所包括的每一个成员小区，根据每一个该成员小区的终端的参考信号接收功率从每一个该成员小区的预设权值中确定每一个该成员小区的成员目标广播波束权值，将每一个该成员小区的该成员目标广播波束权值组合为该子网目标广播波束权值集合。其中，任一个成员小区的成员目标广播波束权值所对应的小区覆盖高于该任一个成员小区的预设权值中除该成员目标广播波束权值之外的其他预设权值所对应的小区覆盖；或者，
可选地，该对于该一个或多个子网中的任意一个第一子网，根据该第一子网所包括的成员小区的小区覆盖和该第一子网所包括的成员小区的小区间干扰在该成员小区的预设权值中确定该第一子网的子网目标广播波束权值集合，包括：对于该第一子网所包括的每一个成员小区，根据每一个该成员小区内的终端的参考信号接收功率从每一个该成员小区的预设权值中确定每一个该成员小区的成员备选广播波束权值，其中，任一个成员小区的成员备选广播波束权值所对应的小区覆盖高于该任一个成员小区的预设权值中除该成员备选广播波束权值之外的其他预设权值所对应的小区覆盖；
根据该第一子网所包括的每一个该成员小区内的终端在成员备选广播波束权值条件下的信号与干扰加噪声比从每一个该成员小区的该成员备选广播波束权值中确定该子网目标广播波束权值集合，其中，该子网目标广播波束权值集合所对应的小区间干扰小于其他子网广播波束权值集合所对应的小区间干扰，该其他子网广播波束权值为每一个成员小区的该成员备选广播波束权值中除该成员目标广播波束权值之外的其他成员备选广播波束权值所组成的子网广播波束权值。
在一实施例中，示例性地，小区覆盖可以根据小区的信号接收参数(例如参考信号接收功率)确定或者表征，小区间的干扰可以通过信号质量参数(例如信号与干扰加噪声比)确定或者表征。
在一实施例中，分割后得到的子网中，每个子网可能包括一个或多个成员小区，其中，有的成员小区可能没有邻区，例如一个小区可以独自构成一个子网并且该小区也没有邻区的情况。对于没有邻区的成员小区，示例性地，可以只根据成员小区内的终端的信号接收参数确定该成员小区的目标广播波束权值，例如上述的方法。
在一实施例中，如果子网中包括了多个成员小区，那么这些成员小区都是存在至少一个邻区的，对于有邻区的成员小区，示例性地，可以根据成员小区内的终端的信号接收参数和该成员小区的信号质量参数确定该成员小区所在子网的子网目标广播波束权值。对于有邻区的成员小区，在进行网优时，既要考虑小区覆盖，又要考虑小区间的干扰，所以可以根据该成员小区内的终端的信号接收参数和该成员小区的信号质量参数确定子网目标广播波束权值。
可选地，该对于该第一子网所包括的每一个成员小区，根据每一个该成员小区的终端的参考信号接收功率从每一个该成员小区的预设权值中确定每一个该成员小区的成员目标广播波束权值，包括：
对于每一个成员小区，遍历该成员小区的每一个预设权值，得到每一个预设权值所对应的成员小区内的终端的服务小区参考信号接收功率；
对于该成员小区中的每一个预设权值，将该预设权值所对应的所有该服务小区参考信号接收功率所组成的参考信号接收功率区间划分为第一指定数量的等份；在一实施例中，第一指定数量可以是10、100或1000等数值。
对于该成员小区中的每一个预设权值，分别确定该每个预设权值所对应的每一个该服务小区参考信号接收功率落入每个该等份的频率，确定频率累计分布为第一指定频率时所对应的最大参考信号接收功率；在一实施例中，第一指定频率可以是0.3～0.6中的任意一个数值，例如，可以是0.3、0.4、0.5或者0.6等。
对于每一个成员小区，将最大的该最大参考信号接收功率所对应的预设权值作为该成员小区的该成员目标广播波束权值。
可选地，对于该第一子网所包括的每一个成员小区，根据每一个该成员小区内的终端的参考信号接收功率从每一个该成员小区的预设权值中确定每一个该成员小区的成员备选广播波束权值，包括：
对于每一个成员小区，遍历该成员小区的每一个预设权值，得到每一个预设权值所对应的成员小区内的终端的服务小区参考信号接收功率；
对于该成员小区中的每一个预设权值，将该预设权值所对应的所有该服务小区参考信号接收功率所组成的参考信号接收功率区间划分为第二指定数量的等份；在一实施例中，由于可能会有多个终端将一个成员小区作为自己的服务小区，所以一个成员小区在一个预设权值的条件下会对应多个终端的服务小区参考信号接收功率，这些终端的服务小区参考信号接收功率中，最小值与最大值所构成的区间就是该成员小区在该预设权值条件下的参考信号接收功率区间。第二指定数量可以是10、100或1000等数值。
对于该成员小区中的每一个预设权值，分别确定该每个预设权值所对应的每一个该服务小区参考信号接收功率落入每个该等份的频率，确定频率累计分布为第二指定频率时所对应的最大参考信号接收功率；在一实施例中，第二指定频率可以是0.3～0.6中的任意值，例如0.3、0.4、0.5或0.6等。
对于每一个成员小区，按数值从高到低对该成员小区所对应的多个该最大参考信号接收功率排序，将排序靠前的一个或多个该最大参考信号接收功率所对应的一个或多个预设权值作为该成员小区的该成员备选广播波束权值。
可选地，针对每一个成员小区，可以根据该成员小区在已知的权值(例如当前生效的广播波束权值)的条件下所得到的该成员小区的信号参数估计出该成员小区在预设权值中的其他广播波束权值条件下的该成员小区的信号参数，例如，可以根据已经生效的权值所对应的信号参数(可测量或者可计算)估计其他未生效的权值所对应的信号参数。
在一实施例中，该成员小区在当前广播波束权值条件下的信号参数可以是直接测量得到的，也可以是直接处理或者筛选测量得到的一些信号参数所得到的。
在本实施例中，“成员小区内的终端”可以理解为将一个成员小区作为服务小区的终端。由于一个成员小区内的终端可以是一个或多个，所以一个成员小区 会对应一个或多个终端的测量数据，例如对应一个或多个终端测量所得到的参考信号接收功率。
可选地，对于每个成员小区所对应的预设权值中所包括的第一预设权值和第二预设权值，第二预设权值所对应的第一终端的服务小区参考信号接收功率为第一预设权值所对应的该第一终端的服务小区参考信号接收功率与第一天线增益之和，其中，该第一预设权值所对应的该第一终端的该服务小区参考信号接收功率是测量得到的，该第一天线增益是根据该第二预设权值、该第一预设权值和该第一终端的波达方向所确定的。
在一实施例中，新的预设权值所对应的终端的服务小区参考信号接收功率可以是根据已知预设权值所对应的已知终端的服务小区参考信号接收功率估计得到。其中，已知终端的服务小区参考信号接收功率可以是使用已知预设权值发送波束的条件下，该服务小区内的终端测量得到的。
在一实施例中，“第一预设权值”可以是当前已经生效的一个权值，已经生效的权值所对应的参考信号接收功率是可以测量得到的。“第二预设权值”可以是未生效的一个权值。
可选地，该根据该第一子网所包括的每一个该成员小区内的终端在成员备选广播波束权值条件下的信号与干扰加噪声比从每一个该成员小区的该成员备选广播波束权值中确定该子网目标广播波束权值集合，包括：
对于该第一子网，利用蚁群算法从每一个该成员小区的该成员备选广播波束权值中确定该第一子网的该子网目标广播波束权值集合，其中，该蚁群算法的解为该子网目标广播波束权值集合，每一轮迭代过程中包括了多只蚂蚁，每只蚂蚁的选择结果为一个子网广播波束权值集合，该子网广播波束权值集合中包括了蚂蚁从每个成员小区的该成员备选广播波束权值中所选择的广播波束权值。
可选地，所述利用蚁群算法从每一个所述成员小区的所述成员备选广播波束权值中确定所述第一子网的所述子网目标广播波束权值集合，包括：每只蚂蚁选择该成员备选广播波束权值的概率与该成员备选广播波束权值的期望值呈正相关的关系，该成员备选广播波束权值的期望值与上一轮迭代过程中，选择了该成员备选广播波束权值的蚂蚁所对应的子网广播波束权值集合的子网信号 与干扰加噪声比呈正相关的关系，该第一子网的子网信号与干扰加噪声比是利用函数处理该第一子网的子网广播波束权值集合条件下的成员小区内的终端的信号与干扰加噪声比所得到的。
可选地，在每一轮迭代过程中，每个成员备选广播波束权值的期望值为：上一轮迭代过程中，所有选择了该成员备选广播波束权值的蚂蚁所对应的子网广播波束权值集合的子网信号与干扰加噪声比的平均值。
可选地，该第一子网的子网信号与干扰加噪声比是利用函数处理该第一子网的子网广播波束权值集合条件下的成员小区内的终端的信号与干扰加噪声比所得到的，包括：
对于该第一子网，在每一轮迭代过程开始之前，对于在上一轮迭代过程中的每一个蚂蚁，确定每一个该蚂蚁所选择的子网广播波束权值集合条件下的终端的信号与干扰加噪声比；
将该第一子网的所有该终端的信号与干扰加噪声比所组成的区间划分为第三指定数量的等份；在一实施例中，一个成员小区内可能有多个终端，每个终端在每个预设权值的条件下都对应了一个“信号与干扰加噪声比”。则第一子网可能对应了多个信号与干扰加噪声比，这些信号与干扰加噪声比中，最小值与最大值所构成的区间就是第一子网的所有该终端的信号与干扰加噪声比所组成的区间。
对于该第一子网，分别确定该终端的信号与干扰加噪声比落入每个该等份的频率，确定频率累计分布为第三指定频率时所对应的最大信号与干扰加噪声比，将该最大信号与干扰加噪声比作为该子网广播波束权值集合所对应的子网信号与干扰加噪声比。第三指定数量可以是10、100或1000等数量。第三指定频率可以是0.3～0.6中的任意数值，例如，可以是0.3、0.4、0.5或0.6等数值。
可选地，该成员小区内的终端的信号与干扰加噪声比为：该终端所在的服务小区的参考信号接收功率，与，该终端所测量得到的该服务小区的邻区的邻区参考信号接收功率之和加白噪声功率，的比。
可选地，对于一个成员小区所对应的成员备选广播波束权值中所包括的第一成员备选广播波束权值和第二成员备选广播波束权值，第一成员备选广播波束权值所对应的第一终端的该邻区参考信号接收功率为第二成员备选广播波束 权值所对应的该第一终端的该邻区参考信号接收功率与第二天线增益之和，其中，该第二成员备选广播波束权值所对应的该第一终端的该邻区参考信号接收功率是该第一终端测量得到的，该第二天线增益是根据该第一成员备选广播波束权值、该第二成员备选广播波束权值和该第一终端的波达方向所确定的。
在一实施例中，如果该“第二成员备选广播波束权值”是未生效的权值，则“第二成员备选广播波束权值”可以是根据已知权值条件下的已知邻区参考信号接收功率所估计得到的，该已知邻区参考信号接收功率可以是测量得到的。如果该“第二成员备选广播波束权值”是已经生效的权值，则也可以测量得到该“第二成员备选广播波束权值”所对应的邻区参考信号接收功率。该“第一成员备选广播波束权值”可以是未生效的权值。
可选地，该利用蚁群算法从每一个该成员小区的该成员备选广播波束权值中确定该第一子网的该子网目标广播波束权值集合，包括：
在一轮迭代过程开始之前，更新每个成员小区中的每个成员备选广播波束权值的信息素浓度，其中，该成员备选广播波束权值被蚂蚁选择的概率与该成员备选广播波束权值的该信息素浓度呈正相关的关系，该信息素的浓度与该成员备选广播波束权值在该上一轮迭代过程中被蚂蚁选择的次数呈正相关的关系。
可选地，该利用蚁群算法从每一个该成员小区的该成员备选广播波束权值中确定该第一子网的该子网目标广播波束权值集合，还包括：
达到预设的迭代次数之后，将多个该子网广播波束权值集合中，最大的子网信号与干扰加噪声比所对应的子网广播波束权值集合作为该子网目标广播波束权值集合。在一实施例中，每一轮迭代过程中，每个蚂蚁都选择了一个子网广播波束权值集合，由于每个子网广播波束权值集合对应了一个子网信号与干扰加噪声比，所以每一轮迭代过程中产生了多个子网信号与干扰加噪声比；子网信号与干扰加噪声比越大，则说明该子网广播波束权值集合越优，所以可以选择所有迭代过程中的最大的子网信号与干扰加噪声比所对应的子网广播波束权值集合作为该子网的子网目标广播波束权值集合。
可选地，该第一小区与该第二小区的小区间重叠覆盖程度为第一重叠覆盖度与第二重叠覆盖度的平均值，其中，该第一重叠覆盖度为该第一小区相对于 该第二小区的重叠覆盖度，该第二重叠覆盖度为该第二小区相对于该第一小区的重叠覆盖度。
可选地，该第一重叠覆盖度为：满足第一条件的测量报告样本数与该第一小区中满足第二条件的测量报告样本数的比值，其中，该第一条件包括：该第一小区的参考信号接收功率大于或等于第一阈值，并且，该第二小区的参考信号接收功率大于或等于第二阈值，并且，该第二小区的参考信号接收功率与该第一小区的参考信号接收功率的差值的绝对值大于或等于第三阈值，该第二条件包括：该第一小区的参考信号接收功率大于或等于该第一阈值；在本实施方式中，第一小区可以是服务小区，第二小区可以是该服务小区的邻区。
可选地，该第二重叠覆盖度为：满足该第三条件的测量报告样本数与该第二小区中满足第四条件的测量报告样本数的比值，其中，该第三条件包括：该第二小区的参考信号接收功率大于或等于第四阈值，并且，该第一小区的参考信号接收功率大于或等于第五阈值，并且，该第一小区的参考信号接收功率与该第二小区的参考信号接收功率的差值的绝对值大于或等于第六阈值，该第四条件包括：该第二小区的参考信号接收功率大于或等于该第四阈值。在本实施方式中，第二小区可以是服务小区，第一小区可以是该服务小区的邻区。
可选地，在该将确定后的该子网目标广播波束权值集合发送至该第一子网之后，该方法还包括：
按照预设指标对该子网目标广播波束权值集合进行评估，在评估结果不满足该预设指标的情况下，回退该子网目标广播波束权值集合为初始权值集合；
在该评估结果满足该预设指标的情况下，按照发送至该第一子网的该子网目标广播波束权值集合发送广播波束。
可选地，更新子网目标广播波束权值可以是恢复权值为初始值。
可选地，该预设指标包括以下至少之一：无线资源控制(radio resource control，RRC)连接建立成功率指标、系统内切换出成功率指标、无线掉线率指标、频谱效率指标、平均激活用户数指标。
可选地，该方法还包括：根据确定的该成员目标广播波束权值调整对应成员小区的成员业务波束权值，得到成员目标业务波束权值，其中，该成员目标业务波束权值用于指示对应的目标小区根据该成员目标业务波束权值发送业务 波束。
可选地，该根据确定的该成员目标广播波束权值调整对应成员小区的成员业务波束权值，得到成员目标业务波束权值，包括以下至少之一：
将该成员目标广播波束权值的方位角作为该成员业务波束权值的方位角，得到该成员目标业务波束权值；
将该成员目标业务波束权值的下倾角范围覆盖该成员广播波束权值的下倾角，得到该成员目标业务波束权值。
在一实施例中，成员目标业务波束权值的下倾角范围覆盖该成员目标广播波束权值的下倾角可以指：一个成员小区可能配置了多个业务波束，这些业务波束有各自的下倾角，这些不同业务波束的下倾角会构成一个下倾角范围，则该成员小区的广播波束权值的下倾角需要在该下倾角范围之内，即，业务波束权值的下倾角范围覆盖广播波束权值的下倾角。
可选地，按照预设的波束数量和预设的波束下倾角间距确定该成员目标业务波束权值的下倾角。例如，预设的波束下倾角间距为2度或者3度或者4度或者5度等，同一小区的不同的业务波束可以按照相同的下倾角间距连续分布。
上述实施例的方法可借助软件加必需的通用硬件平台的方式来实现，也可以通过硬件实现。本申请可以以软件产品的形式体现出来，该计算机软件产品存储在一个计算机可读的存储介质(如ROM/RAM、磁碟、光盘)中，包括多个指令用以使得一台终端设备(可以是手机，计算机，服务器，或者网络设备等)执行本申请多个实施例所述的方法。
在本实施例中还提供了一种权值的发送装置，该装置用于实现上述实施例及实施方式，已经进行过说明的不再赘述。如以下所使用的，术语“模块”可以实现预定功能的软件和/或硬件的组合。尽管以下实施例所描述的装置可以以软件来实现，但是硬件，或者软件和硬件的组合的实现也是可能并被构想的。
图3是根据本发明实施例的权值的发送装置的结构框图，如图3所示，该装置包括：
分割模块31，设置为分割多个小区，得到一个或多个子网，其中，该子网包括一个或多个该小区，对于该子网所包括的任意一个第一成员小区，该第一成员小区与该第一成员小区所在的子网中的第二成员小区的小区间重叠覆盖程 度高于预设的程度阈值，该第二成员小区为该第一成员小区的邻小区；
确定模块33，设置为对于该一个或多个子网中的任意一个第一子网，根据以下至少之一在该成员小区的预设权值中确定该第一子网的子网目标广播波束权值集合：该第一子网所包括的成员小区的小区覆盖、该第一子网所包括的成员小区的小区间干扰，其中，该子网目标广播波束权值集合包括该第一子网中的每一个该成员小区的成员目标广播波束权值；
发送模块35，设置为将确定后的该子网目标广播波束权值集合发送至该第一子网，其中，该子网目标广播波束权值集合用于指示该第一子网中的成员小区根据该子网目标广播波束权值集合中对应的该成员目标广播波束权值发送广播波束。
通过上述模块，由于将多个小区划分为一个或多个子网，根据小区覆盖和/或小区间干扰确定任意一个子网的目标广播波束权值，因此，可以解决相关技术中网优效率较低的问题，达到提高网优效率的效果。
上述多个模块是可以通过软件或硬件来实现的，对于后者，可以通过以下方式实现，但不限于此：上述模块均位于同一处理器中；或者，上述多个模块以任意组合的形式分别位于不同的处理器中。
可选地，该对于该一个或多个子网中的任意一个第一子网，根据该第一子网所包括的成员小区的小区覆盖在该成员小区的预设权值中确定该第一子网的子网目标广播波束权值集合，包括：对于该第一子网所包括的每一个成员小区，根据每一个该成员小区的终端的参考信号接收功率从每一个该成员小区的预设权值中确定每一个该成员小区的成员目标广播波束权值，将每一个该成员小区的该成员目标广播波束权值组合为该子网目标广播波束权值集合，其中，任一个成员小区的成员目标广播波束权值所对应的小区覆盖高于该任一个成员小区的预设权值中除该成员目标广播波束权值之外的其他预设权值所对应的小区覆盖；或者，
可选地，该对于该一个或多个子网中的任意一个第一子网，根据该第一子网所包括的成员小区的小区覆盖和该第一子网所包括的成员小区的小区间干扰在该成员小区的预设权值中确定该第一子网的子网目标广播波束权值集合，包括：对于该第一子网所包括的每一个成员小区，根据每一个该成员小区内的终 端的参考信号接收功率从每一个该成员小区的预设权值中确定每一个该成员小区的成员备选广播波束权值，其中，任一个成员小区的成员备选广播波束权值所对应的小区覆盖高于该任一个成员小区的预设权值中除该成员备选广播波束权值之外的其他预设权值所对应的小区覆盖；
根据该第一子网所包括的每一个该成员小区内的终端在该成员备选广播波束权值条件下的信号与干扰加噪声比从每一个该成员小区的该成员备选广播波束权值中确定该子网目标广播波束权值集合，其中，该子网目标广播波束权值集合所对应的小区间干扰小于其他子网广播波束权值集合所对应的小区间干扰，该其他子网广播波束权值为每一个成员小区的该成员备选广播波束权值中除该成员目标广播波束权值之外的其他成员备选广播波束权值所组成的子网广播波束权值。
可选地，该对于该第一子网所包括的每一个成员小区，根据每一个该成员小区的终端的参考信号接收功率从每一个该成员小区的预设权值中确定每一个该成员小区的成员目标广播波束权值，包括：
对于每一个成员小区，遍历该成员小区的每一个预设权值，得到每一个预设权值所对应的成员小区内的终端的服务小区参考信号接收功率；
对于该成员小区中的每一个预设权值，将该预设权值所对应的所有该服务小区参考信号接收功率所组成的参考信号接收功率区间划分为第一指定数量的等份；
对于该成员小区中的每一个预设权值，分别确定该每个预设权值所对应的每一个该服务小区参考信号接收功率落入每个该等份的频率，确定频率累计分布为第一指定频率时所对应的最大参考信号接收功率；
对于每一个成员小区，将最大的该最大参考信号接收功率所对应的预设权值作为该成员小区的该成员目标广播波束权值。
可选地，对于该第一子网所包括的每一个成员小区，根据每一个该成员小区内的终端的参考信号接收功率从每一个该成员小区的预设权值中确定每一个该成员小区的成员备选广播波束权值，包括：
对于每一个成员小区，遍历该成员小区的每一个预设权值，得到每一个预设权值所对应的成员小区内的终端的服务小区参考信号接收功率；
对于该成员小区中的每一个预设权值，将该预设权值所对应的所有该服务小区参考信号接收功率所组成的参考信号接收功率区间划分为第二指定数量的等份；
对于该成员小区中的每一个预设权值，分别确定该每个预设权值所对应的每一个该服务小区参考信号接收功率落入每个该等份的频率，确定频率累计分布为第二指定频率时所对应的最大参考信号接收功率；
对于每一个成员小区，按数值从高到低对该成员小区所对应的多个该最大参考信号接收功率排序，将排序靠前的一个或多个该最大参考信号接收功率所对应的一个或多个预设权值作为该成员小区的该成员备选广播波束权值。
可选地，对于一个成员小区所对应的预设权值中所包括的第一预设权值和第二预设权值，第二预设权值所对应的第一终端的服务小区参考信号接收功率为第一预设权值所对应的该第一终端的服务小区参考信号接收功率与第一天线增益之和，其中，该第一预设权值所对应的该第一终端的该服务小区参考信号接收功率是测量得到的，该第一天线增益是根据该第二预设权值、该第一预设权值和该第一终端的波达方向所确定的。
可选地，该根据该第一子网所包括的每一个该成员小区内的终端在成员备选广播波束权值条件下的信号与干扰加噪声比从每一个该成员小区的该成员备选广播波束权值中确定该子网目标广播波束权值集合，包括：
对于该第一子网，利用蚁群算法从每一个该成员小区的该成员备选广播波束权值中确定该第一子网的该子网目标广播波束权值集合，其中，该蚁群算法的解为该子网目标广播波束权值集合，每一轮迭代过程中包括了多只蚂蚁，每只蚂蚁的选择结果为一个子网广播波束权值集合，该子网广播波束权值集合中包括了蚂蚁从每个成员小区的该成员备选广播波束权值中所选择的广播波束权值。
可选地，该利用蚁群算法从每一个该成员小区的该成员备选广播波束权值中确定该第一子网的该子网目标广播波束权值集合，包括：
每只蚂蚁选择该成员备选广播波束权值的概率与该成员备选广播波束权值的期望值呈正相关的关系，该成员备选广播波束权值的期望值与上一轮迭代过程中，选择了该成员备选广播波束权值的蚂蚁所对应的子网广播波束权值集合 的子网信号与干扰加噪声比呈正相关的关系，该第一子网的子网信号与干扰加噪声比是利用函数处理该第一子网的子网广播波束权值集合条件下的成员小区内的终端的信号与干扰加噪声比所得到的。
可选地，在每一轮迭代过程中，每个成员备选广播波束权值的期望值为：上一轮迭代过程中，所有选择了该成员备选广播波束权值的蚂蚁所对应的子网广播波束权值集合的子网信号与干扰加噪声比的平均值。
可选地，该第一子网的子网信号与干扰加噪声比是利用函数处理该第一子网的子网广播波束权值集合条件下的成员小区内的终端的信号与干扰加噪声比所得到的，包括：
对于该第一子网，在每一轮迭代过程开始之前，对于在上一轮迭代过程中的每一个蚂蚁，确定每一个该蚂蚁所选择的子网广播波束权值集合条件下的终端的信号与干扰加噪声比；
将该第一子网的所有该终端的信号与干扰加噪声比所组成的区间划分为第三指定数量的等份；
对于该第一子网，分别确定该终端的信号与干扰加噪声比落入每个该等份的频率，确定频率累计分布为第三指定频率时所对应的最大信号与干扰加噪声比，将该最大信号与干扰加噪声比作为该子网广播波束权值集合所对应的子网信号与干扰加噪声比。
可选地，该成员小区内的终端的信号与干扰加噪声比为：该终端所在的服务小区的参考信号接收功率，与，该终端所测量得到的该服务小区的邻区的邻区参考信号接收功率之和加白噪声功率，的比。
可选地，对于成员小区所对应的成员备选广播波束权值中所包括的第一成员备选广播波束权值和第二成员备选广播波束权值，第一成员备选广播波束权值所对应的第一终端的该邻区参考信号接收功率为第二成员备选广播波束权值所对应的该第一终端的该邻区参考信号接收功率与第二天线增益之和，其中，该第二成员备选广播波束权值所对应的该第一终端的该邻区参考信号接收功率是该第一终端测量得到的，该第二天线增益是根据该第一成员备选广播波束权值、该第二成员备选广播波束权值和该第一终端的波达方向所确定的。
可选地，该利用蚁群算法从每一个该成员小区的该成员备选广播波束权值 中确定该第一子网的该子网目标广播波束权值集合，还包括：
在一轮迭代过程开始之前，更新每个成员小区中的每个成员备选广播波束权值的信息素浓度，其中，该成员备选广播波束权值被蚂蚁选择的概率与该成员备选广播波束权值的该信息素浓度呈正相关的关系，该信息素的浓度与该成员备选广播波束权值在该上一轮迭代过程中被蚂蚁选择的次数呈正相关的关系。
可选地，该利用蚁群算法从每一个该成员小区的该成员备选广播波束权值中确定该第一子网的该子网目标广播波束权值集合，还包括：
达到预设的迭代次数之后，将多个该子网广播波束权值集合中，最大的子网信号与干扰加噪声比所对应的子网广播波束权值集合作为该子网目标广播波束权值集合。
可选地，该第一小区与该第二小区的小区间重叠覆盖程度为第一重叠覆盖度与第二重叠覆盖度的平均值，其中，该第一重叠覆盖度为该第一小区相对于该第二小区的重叠覆盖度，该第二重叠覆盖度为该第二小区相对于该第一小区的重叠覆盖度。
可选地，该第一重叠覆盖度为：满足第一条件的测量报告样本数与该第一小区中满足第二条件的测量报告样本数的比值，其中，该第一条件包括：该第一小区的参考信号接收功率大于或等于第一阈值，并且，该第二小区的参考信号接收功率大于或等于第二阈值，并且，该第二小区的参考信号接收功率与该第一小区的参考信号接收功率的差值的绝对值大于或等于第三阈值，该第二条件包括：该第一小区的参考信号接收功率大于或等于该第一阈值；或者，
该第二重叠覆盖度为：满足第三条件的测量报告样本数与该第二小区中满足第四条件的测量报告样本数的比值，其中，该第三条件包括：该第二小区的参考信号接收功率大于或等于第四阈值，并且，该第一小区的参考信号接收功率大于或等于第五阈值，并且，该第一小区的参考信号接收功率与该第二小区的参考信号接收功率的差值的绝对值大于或等于第六阈值，该第四条件包括：该第二小区的参考信号接收功率大于或等于该第四阈值。
可选地，在该将确定后的该子网目标广播波束权值集合发送至该第一子网之后，该装置还包括：
评估模块，设置为按照预设指标对该子网目标广播波束权值集合进行评估，在评估结果不满足该预设指标的情况下，回退该子网目标广播波束权值集合为初始权值集合；在该评估结果满足该预设指标的情况下，按照发送至该第一子网的该子网目标广播波束权值集合发送广播波束。
可选地，该预设指标包括以下至少之一：无线资源控制连接建立成功率指标、系统内切换出成功率指标、无线掉线率指标、频谱效率指标、平均激活用户数指标。
可选地，该装置还包括：调整模块，设置为根据确定的该成员目标广播波束权值调整对应成员小区的成员业务波束权值，得到成员目标业务波束权值，其中，该成员目标业务波束权值用于指示对应的目标小区根据该成员目标业务波束权值发送业务波束。
可选地，该根据确定的该成员目标广播波束权值调整对应成员小区的成员业务波束权值，得到成员目标业务波束权值，包括以下至少之一：将该成员目标广播波束权值的方位角作为该成员业务波束权值的方位角，得到该成员目标业务波束权值；将该成员目标业务波束权值的下倾角范围覆盖该成员广播波束权值的下倾角，得到该成员目标业务波束权值。
可选地，按照预设的波束数量和预设的波束下倾角间距确定该成员目标业务波束权值的下倾角。
可选实施方式
为了使4G LTE/5G NR系统在多样化场景中具有最优覆盖及频谱效率，本实施例提出了4G LTE/5G NR系统中一种自适应调整天线权值的方法。该方法根据用户分布、测量报告(Measurement Report，MR)生成每个小区的同步信号和PBCH块(synchronization signal and PBCH block，SSB)波束权值和信道状态信息参考信号(channel state information reference signal，CSI-RS)波束权值，其中，PBCH的英文全称是Physical Broadcast Channel，中文全称是物理广播信道。
在一实施例中，SSB波束权值相当于一种广播波束权值。CSI-RS波束权值相当于一种业务波束权值。
对于4G LTE/5G NR超密集同频组网的天线权值联合优化，本实施例提供了一种方法，图4是根据本申请可选实施方式的网优方法的流程图，如图4所示， 包括：
在网管侧进行优化区域选择及任务配置，并把任务下发到网元。优化区域可以根据网优人员指定，也可以通过工具自动识别，任务配置选中需要优化的目标，激活任务。
网元进行MR数据收集和到达角(Direction of Arrival，DOA)数据测量，并把数据上报给网管。
网管根据收集的数据进行子网分割和最优权值估算。
网管下发新权值到网元生效，网元进行关键性能指标(Key Performance Indicator，KPI)采集并上报给网管。
网管根据收集的KPI信息进行权值评估，若评估通过，下发权值更新到网元；若评估不通过，下发权值回退到网元。
图5是根据本申请可选实施方式的权值的发送方法的流程图，如图5所示，包括：
开始。
数据收集，例如收集终端上报的测量报告。
子网分割，其中，示例性地，子网分割的过程可以如下：
为了提升蚁群算法的优化效率，根据收集的MR数据进行子网分割，子网分割操作根据MR测量结果计算每个小区和其邻小区的重叠覆盖度，以重叠覆盖度来反映两小区的关联紧密程度，重叠覆盖度越大，则认为关系越紧密，每个子网限定小区个数为CellNumThr，默认50，可配。子网分割步骤如下所示。
可选地，根据以下公式计算小区间重叠覆盖度：
例如由A和B两小区，小区A计算它与小区B的重叠覆盖度方法：
Figure PCTCN2021076147-appb-000001
假设A为服务小区，B为小区A的邻区，记RSRPi为服务小区参考信号接收功率(Reference Signal Receiving Power，RSRP)，RSRPj为邻区RSRP：
条件1：RSRPi大于或等于“服务小区覆盖RSRP门限ucOverlapSrvThd”；
条件2：RSRPj大于或等于“邻区重叠覆盖RSRP门限ucOverlapNbrThd”；
条件3：abs(RSRPj-RSRPi)大于或等于“邻区重叠覆盖RSRP差值门限ucOverlapNbrDifferThd”，其中，abs()表示取绝对值。
同样的方法计算小区B与小区A的重叠覆盖度记为C BA，如下：
Figure PCTCN2021076147-appb-000002
其中，假设B为服务小区，A为小区B的邻区，记RSRPi为服务小区RSRP，RSRPj为邻区RSRP：
条件1：RSRPi大于或等于“服务小区覆盖RSRP门限ucOverlapSrvThd”；
条件2：RSRPj大于或等于“邻区重叠覆盖RSRP门限ucOverlapNbrThd”；
条件3：abs(RSRPj-RSRPi)大于或等于“邻区重叠覆盖RSRP差值门限ucOverlapNbrDifferThd”，其中，abs()表示取绝对值；
最终得到小区A和小区B的关联程度：
Figure PCTCN2021076147-appb-000003
基于以上方法，可以根据用户设备(User Equipment，UE)数据计算出多个小区间的关联关系。假如有15个小区A～O，则可以构成如图6所示的加权连通图，图6是根据本申请可选实施方式的加权连通图，图6的边即是两小区的关联程度。
然后，根据小区加权连通图，通过普里姆算法生成子网。可选地，可以通过不断提高小区加权连通图中的不同小区之间的关联程度的熔断门限生成最大生成树，方式如下：
子网的分割方法，基本原则是将联系紧密的小区划分到一个子集，可以采用图论中的普里姆算法先求得最大生成树，最大生成树能保证所有小区依然处于连通状态，然后再基于最大生成树进行分割，普里姆求解最大生成树算法流程如下：
1).输入：一个加权连通图，其中顶点集合为V，边集合为E。
2).初始化：Vnew＝{x}，其中x为集合V中的任一节点(起始点)，Enew＝{}，为空；
3).重复下列操作，直到Vnew＝V：
a.在集合E中选取权值最大的边<u,v>，其中u为集合Vnew中的元素，而v不在Vnew集合当中，并且v∈V(如果存在有多条满足前述条件即具有相同权值的边，则可任意选取其中之一)。
b.将v加入集合Vnew中，将<u,v>边加入集合Enew中。
4).输出：使用集合Vnew和Enew来描述所得到的最大生成树。
图7是根据本申请可选实施方式的最大生成树示意图，如图7所示，按边权重小于门限(门限可配)的边熔断，例如将权重小于0.2的边熔断，得到了图8中所示的内容，图8是根据本申请可选实施方式的熔断示意图，在图8中，子网内最多包括7个小区，每个子网均满足子网内最多包括9个小区(子网所包括的最多小区数门限可配)的要求。在一实施例中，若实际出现分割后一些子网小区数超过最大小区数要求，则说明熔断门限设置不合理，需要提高熔断门限。由于图7中所述的子网中的小区数量超过了预设的数值(例如可以是9)，所以，可以不断提高熔断门限使得分割后的每个子网所包含的小区数小于或等于子网最大小区数门限。
然后，以RSRP CDF50最大化为代价函数遍历得到每个小区TOP N个最优SSB波束权值，其中，CDF(cumulative distribution function)为累积分布函数；然后以信号与干扰加噪声比(Signal to Interference plus Noise Ratio，SINR)CDF50最大化为代价函数通过蚁群算法进行SSB波束权值寻优，示例性地，步骤如下：
对于子网内的每个小区以RSRP CDF50最大化为代价函数通过遍历方法进行SSB波束权值寻优，对于存在邻区关系的小区以SINR CDF50最大化为代价函数通过蚁群算法进行SSB波束权值寻优。本步骤包括以下步骤：
1)子网内每个小区根据用户DOA、MR数据以RSRP CDF50最大化为代价函数，通过遍历方法得到每个小区TOP N个最优权值，RSRP CDF50代价函数计算公式如下所示。
新权值下的UE在服务小区的RSRP基于MR上报的RSRP及新权值下的天 线增益计算得到。假定UEi在权值k对应的MR上报计为RSRPi,k，该UE对应的DOA角度为(h,v)，那么在选择新权值j时，该UE的RSRPi,j计算方法如下：
RSRPi,j＝RSRPi,k+AntGainTbl[j][h][v]-AntGainTbl[k][h][v]
其中：AntGainTbl为保存的3D天线增益表。
该UE测得邻区RSRP的估计方法相同，该UE在多个邻区的DOA信息由邻区协助测量得到。
把所有UE更新后的RSRP进行从小到大排序，并把RSRP区间分割成1000等份RSRP小区间，统计落入每个RSRP小区间的频率，计算RSRP累积分布为0.5时对应RSRP小区间中最大RSRP值作为代价函数值，通过遍历所有权值，计算每个权值的RSRP CDF50值，取最大的TOP N个权值作为后续SINR CDF50优化时的候选权值。
2)子网内所有小区根据用户DOA、MR数据以SINR CDF50最大化为代价函数，通过蚁群算法得到子网内所有小区联合最优权值。SINR CDF50代价函数计算公式如下所示。
UE SINR计算方法：
Figure PCTCN2021076147-appb-000004
其中：
可选地，服务小区RSRP，邻区RSRP计算公式同步骤1)。
可选地，计算SINR前需要先将RSRP转化为线性值。
可选地，白噪声功率：-174dBm+10*log(30*1000)＝-130dBm，考虑UE接收机噪声系数，设定白噪声功率为-125dBm。
可选地，SINR计算需要做最大/最小值保护，-20dB≤SINR≤40dB。
可选地，上述UE SINR的计算方法中的“邻区”指的是每个终端上报的MR测量报告中该终端测量到的所有邻区。
在一实施例中，每个终端在一种权值的条件下对应一个UE SINR，由于一个子网内可能有多个小区，每个小区又对应了多个备选权值，每个小区内又可 能有多个终端，所以，一个子网可以对应多个UE SINR，把一个子网所对应的所有小区内的所有终端的UE SINR进行从小到大排序，并把SINR区间分割成1000等份SINR小区间，统计落入每个SINR小区间的频率，计算SINR累积分布为0.5时对应SINR小区间中最大SINR值作为代价函数值，通过蚁群算法，计算所有小区联合搜索权值，每个小区都从步骤1)得到的候选权值中进行搜索。
图9是蚁群算法的算法流程图，如图9所示，包括：
开始。
初始化参数；其中，需要初始化的参数包括蚂蚁数量m，信息素重要程度因子α，启发函数重要程度因子β，信息素挥发因子ρ，信息素强度系数Q、和最大迭代次数Iter_Max。
构建解空间；以一个子网中包括了4个成员小区为例，则该子网的子网目标广播波束权值的基本解定义如下：
W＝[Wcell0,Wcell1,Wcell2,Wcell3]
其中每个小区的权值为选择的N个备选权值之一(即上述的候选权值)。每个小区每个权值的选择概率由如下公式决定：
Figure PCTCN2021076147-appb-000005
其中：
-P i k表示蚂蚁k选择权值i的概率；
-τ i(t)表示t时刻，权值i上的信息素浓度；
-η i(t)为权值期望值，表示t时刻，权值i的期望程度。
由以上公式可知，权值i的信息素浓度和期望值越高，其被选中的概率越高。期望值η i(t)定义为权值解空间下所有小区下代价函数计算得到的价值，根据搜索目的的不同，η i(t)的处理略有所不同：
Figure PCTCN2021076147-appb-000006
每个权值的选择概率基于每个小区维护的权值-信息素浓度-权值期望表格计算得到，信息素浓度初始值为τ 0，权值期望初始化为η0，每个权值的初始选择概率为1/N(N为备选权值个数)。
表1
权值w 信息素浓度τ i(t) 权值期望η i(t) 概率P
W0 τ 0 η0 1/N
W1 τ 0 η0 1/N
... ... ... ...
WN-2 τ 0 η0 1/N
WN-1 τ 0 η0 1/N
表1是权值-信息素浓度-权值期望表，每个小区都需要维护如上一张的表1，在一实施例中，对于所有蚂蚁，在完成一轮迭代后，其中权值期望是该小区所有选择了该权值的蚂蚁计算得到的代价函数平均值。
权值选择采用俄罗斯轮盘赌的概率选择方式。轮盘上不同颜色块代表不同权值，色块宽窄表征了对应权值的选中概率，色块越宽，选中概率越高。
更新信息素。
蚂蚁在释放信息素的同时，多个权值历史累积的信息素也会逐渐消失。设参数ρ(0<ρ<1)表示信息素的挥发程度。因此当所有蚂蚁完成一次搜索后，需要对每个小区的每个权值的信息素浓度进行更新，更新公式如下：
Figure PCTCN2021076147-appb-000007
其中，Δτ k表示第k只蚂蚁在该权值上释放的信息素浓度，若该蚂蚁本次迭代未选择该权值，则其释放的信息素浓度为0；Δτ表示所有蚂蚁在该权值释放的信息素浓度之和。一个权值被蚂蚁选中的越多，其信息素浓度越大。
蚂蚁释放的信息素问题，使用ant cycle system模型，该模型中，Δτ k的计算公式如下：
Figure PCTCN2021076147-appb-000008
其中：Q为常数，表示信息素增加强度系数，该参数取值一定程度上决定了算法的收敛速度，η由价值函数决定。η越大，UE释放的信息素浓度也越高。
本实施例中，首先以RSRP CDF50为代价函数搜索一次权值保留top N个权值用于后续联合优化，这一步可以保证每个小区最优覆盖，然后以SINR CDF50最大化为代价函数联合搜索是为了保证小区间干扰最小。
然后开始迭代，在迭代次数达到预设的最大迭代次数的情况下，停止继续迭代，输出最优解，然后结束算法过程。
可选地，还可以利用每个小区最优SSB波束权值的方位角和倾角联动调整CSI-RS波束权值，在一实施例中，利用最优广播波束信息联动调整业务波束，不仅可以同时调整广播波束与业务波束，还可以避免单独调整业务波束带来的计算开销。其中，示例性地，业务波束可以设为4波束，4波束的水平波宽都固定为50度，垂直波宽都固定为6度；业务波束的方位角取每个SSB的合成方向图(Pattern)的方位角(Azimuth)；业务波束的下倾角度根据SSB Beam tilt调整，规则表如下表2：
表2
SSB_Tilt CSI0_Tilt CSI1_Tilt CSI2_Tilt CSI3_Tilt
-3 -3 0 3 6
0 -3 0 3 6
3 0 3 6 9
6 3 6 9 12
9 3 6 9 12
12 6 9 12 15
举例说明：若优化后最优SSB波束权值为方位角20度，下倾角3度，水平波宽45度，垂直波宽7度，则对应的CSI-RS 4个波束权值分别为CSI_beam0方位角20度，下倾角0度，水平波宽50度，垂直波宽6度；CSI_beam1方位角20度，下倾角3度，水平波宽50度，垂直波宽6度；CSI_beam2方位角20度，下倾角6度，水平波宽50度，垂直波宽6度；CSI_beam3方位角20度，下倾角9度，水平波宽50度，垂直波宽6度。
然后把所有子网优化后的权值进行拼接，然后下发权值生效。权值拼接按照子网ID从小到大，子网内按照基站ID，小区ID从小到大顺序进行权值组合。
然后新权值下发后，对每个子网分别进行KPI评估，若评估通过，进行权值更新；若评估不通过，进行权值回退。
KPI包括：基础KPI和性能KPI；基础KPI包括：RRC连接建立成功率，系统内切换出成功率，无线掉线率等。性能KPI包括：频谱效率(Spectral Efficiency，SE)，平均激活用户数等。
KPI评估按照如下规则进行评估：
区域指标评估：
任务中所有小区在优化前“评估时长”的平均指标＝kbase，
优化后所有小区在优化后“评估时长”的平均指标＝kopt，
满足：满足1，指标分＝0；满足2或4，指标分＝1；满足3，指标分＝-1，
1.kbase*(1-波动门限)<＝kopt<＝kbase*(1+波动门限)
2.kopt>kbase*(1+波动门限)
3.kopt<kbase*(1-波动门限)
4.kopt>＝绝对门限
所有指标分的和>＝0，区域级指标评估通过，所有指标分的和<0，区域级评估未通过。
2)小区级指标评估：
单小区优化前“评估时长”的平均指标＝kbase_cell，
单小区优化后“评估时长”的平均指标＝kopt_cell，
满足：满足1，指标分＝0；满足2或4，指标分＝1；满足3，指标分＝-1，
1.kbase_cell*(1-波动门限)<＝kopt_cell<＝kbase_cell*(1+波动门限)
2.kopt_cell>kbase_cell*(1+波动门限)
3.kopt_cell<kbase_cell*(1-波动门限)
4.kopt_cell>＝绝对门限
所有指标分的和>＝0，该小区的小区级指标评估通过，所有指标分的和<0，该小区的小区级评估未通过。
所有小区的指标通过，则小区级指标评估通过，否则小区级指标评估未通过。
本发明的实施例还提供了一种计算机可读的存储介质，该存储介质中存储有计算机程序，其中，该计算机程序被设置为运行时执行上述任一项方法实施例中的步骤。
可选地，在本实施例中，上述存储介质可以被设置为存储用于执行以下步骤的计算机程序：
S1，分割多个小区，得到一个或多个子网，其中，该子网包括一个或多个该小区，对于该子网所包括的任意一个第一成员小区，该第一成员小区与该第一成员小区所在的子网中的第二成员小区的小区间重叠覆盖程度高于预设的程度阈值，该第二成员小区为该第一成员小区的邻小区。
S2，对于该一个或多个子网中的任意一个第一子网，根据以下至少之一在该成员小区的预设权值中确定该第一子网的子网目标广播波束权值集合：该第一子网所包括的成员小区的小区覆盖、该第一子网所包括的成员小区的小区间干扰，其中，该子网目标广播波束权值集合包括该第一子网中的每一个该成员小区的成员目标广播波束权值。
S3，将确定后的该子网目标广播波束权值集合发送至该第一子网，其中，该子网目标广播波束权值集合用于指示该第一子网中的成员小区根据该子网目标广播波束权值集合中对应的该成员目标广播波束权值发送广播波束。
通过上述步骤，由于将多个小区划分为一个或多个子网，根据小区覆盖和/或小区间干扰确定任意一个子网的目标广播波束权值，因此，可以解决相关技 术中网优效率较低的问题，达到提高网优效率的效果。
可选地，在本实施例中，上述存储介质可以包括：通用串行总线闪存盘(Universal Serial Bus flash disk，U盘)、只读存储器(Read-Only Memory，ROM)、随机存取存储器(Random Access Memory，RAM)、移动硬盘、磁碟或者光盘等多种可以存储计算机程序的介质。
本发明的实施例还提供了一种电子装置，包括存储器和处理器，该存储器中存储有计算机程序，该处理器被设置为运行计算机程序以执行上述任一项方法实施例中的步骤。
可选地，上述电子装置还可以包括传输设备以及输入输出设备，其中，该传输设备和上述处理器连接，该输入输出设备和上述处理器连接。
可选地，在本实施例中，上述处理器可以被设置为通过计算机程序执行以下步骤：
S1，分割多个小区，得到一个或多个子网，其中，该子网包括一个或多个该小区，对于该子网所包括的任意一个第一成员小区，该第一成员小区与该第一成员小区所在的子网中的第二成员小区的小区间重叠覆盖程度高于预设的程度阈值，该第二成员小区为该第一成员小区的邻小区。
S2，对于该一个或多个子网中的任意一个第一子网，根据以下至少之一在该成员小区的预设权值中确定该第一子网的子网目标广播波束权值集合：该第一子网所包括的成员小区的小区覆盖、该第一子网所包括的成员小区的小区间干扰，其中，该子网目标广播波束权值集合包括该第一子网中的每一个该成员小区的成员目标广播波束权值。
S3，将确定后的该子网目标广播波束权值集合发送至该第一子网，其中，该子网目标广播波束权值集合用于指示该第一子网中的成员小区根据该子网目标广播波束权值集合中对应的该成员目标广播波束权值发送广播波束。
通过上述步骤，由于将多个小区划分为一个或多个子网，根据小区覆盖和/或小区间干扰确定任意一个子网的目标广播波束权值，因此，可以解决相关技术中网优效率较低的问题，达到提高网优效率的效果。
可选地，本实施例中的示例可以参考上述实施例及可选实施方式中所描述的示例，本实施例在此不再赘述。
上述的本申请的多个模块或多个步骤可以用通用的计算装置来实现，它们可以集中在单个的计算装置上，或者分布在多个计算装置所组成的网络上，可选地，它们可以用计算装置可执行的程序代码来实现，从而，可以将它们存储在存储装置中由计算装置来执行，并且在一些情况下，可以以不同于此处的顺序执行所示出或描述的步骤，或者将它们分别制作成多个集成电路模块，或者将它们中的多个模块或步骤制作成单个集成电路模块来实现。这样，本申请不限制于任何特定的硬件和软件结合。

Claims (23)

  1. 一种权值的发送方法，包括：
    分割多个小区，得到一个或多个子网，其中，所述子网包括一个或多个所述小区，对于所述子网所包括的任意一个第一成员小区，所述第一成员小区与所述第一成员小区所在的子网中的第二成员小区的小区间重叠覆盖程度高于预设的程度阈值，所述第二成员小区为所述第一成员小区的邻小区；
    对于所述一个或多个子网中的任意一个第一子网，根据以下至少之一在成员小区的预设权值中确定所述第一子网的子网目标广播波束权值集合：所述第一子网所包括的成员小区的小区覆盖、所述第一子网所包括的成员小区的小区间干扰，其中，所述子网目标广播波束权值集合包括所述第一子网中的每一个所述成员小区的成员目标广播波束权值；
    将确定后的所述子网目标广播波束权值集合发送至所述第一子网，其中，所述子网目标广播波束权值集合用于指示所述第一子网中的成员小区根据所述子网目标广播波束权值集合中对应的所述成员目标广播波束权值发送广播波束。
  2. 根据权利要求1所述的方法，其中，所述对于所述一个或多个子网中的任意一个第一子网，根据所述第一子网所包括的成员小区的小区覆盖在所述成员小区的预设权值中确定所述第一子网的子网目标广播波束权值集合，包括：对于所述第一子网所包括的每一个成员小区，根据每一个所述成员小区的终端的参考信号接收功率从每一个所述成员小区的预设权值中确定每一个所述成员小区的成员目标广播波束权值，将每一个所述成员小区的所述成员目标广播波束权值组合为所述子网目标广播波束权值集合，其中，任一个成员小区的成员目标广播波束权值所对应的小区覆盖高于所述任一个成员小区的预设权值中除所述成员目标广播波束权值之外的其他预设权值所对应的小区覆盖；或者，
    所述对于所述一个或多个子网中的任意一个第一子网，根据所述第一子网所包括的成员小区的小区覆盖和所述第一子网所包括的成员小区的小区间干扰在所述成员小区的预设权值中确定所述第一子网的子网目标广播波束权值集合，包括：对于所述第一子网所包括的每一个成员小区，根据每一个所述成员小区内的终端的参考信号接收功率从每一个所述成员小区的预设权值中确定每一个所述成员小区的成员备选广播波束权值，其中，任一个成员小区的成员备 选广播波束权值所对应的小区覆盖高于所述任一个成员小区的预设权值中除所述成员备选广播波束权值之外的其他预设权值所对应的小区覆盖；
    根据所述第一子网所包括的每一个所述成员小区内的终端在成员备选广播波束权值条件下的信号与干扰加噪声比从每一个所述成员小区的所述成员备选广播波束权值中确定所述子网目标广播波束权值集合，其中，所述子网目标广播波束权值集合所对应的小区间干扰小于其他子网广播波束权值集合所对应的小区间干扰，其他子网广播波束权值为每一个成员小区的所述成员备选广播波束权值中除所述成员目标广播波束权值之外的其他成员备选广播波束权值所组成的子网广播波束权值。
  3. 根据权利要求2所述的方法，其中，所述对于所述第一子网所包括的每一个成员小区，根据每一个所述成员小区的终端的参考信号接收功率从每一个所述成员小区的预设权值中确定每一个所述成员小区的成员目标广播波束权值，包括：
    对于每一个成员小区，遍历所述成员小区的每一个预设权值，得到每一个预设权值所对应的成员小区内的终端的服务小区参考信号接收功率；
    对于所述成员小区中的每一个预设权值，将所述预设权值所对应的所有所述服务小区参考信号接收功率所组成的参考信号接收功率区间划分为第一指定数量的等份；
    对于所述成员小区中的每一个预设权值，分别确定所述每一个预设权值所对应的每一个所述服务小区参考信号接收功率落入每个所述等份的频率，确定在频率累计分布为第一指定频率的情况下所对应的最大参考信号接收功率；
    对于每一个成员小区，将最大的所述最大参考信号接收功率所对应的预设权值作为所述成员小区的所述成员目标广播波束权值。
  4. 根据权利要求2所述的方法，其中，所述对于所述第一子网所包括的每一个成员小区，根据每一个所述成员小区内的终端的参考信号接收功率从每一个所述成员小区的预设权值中确定每一个所述成员小区的成员备选广播波束权值，包括：
    对于每一个成员小区，遍历所述成员小区的每一个预设权值，得到每一个预设权值所对应的成员小区内的终端的服务小区参考信号接收功率；
    对于所述成员小区中的每一个预设权值，将所述预设权值所对应的所有所述服务小区参考信号接收功率所组成的参考信号接收功率区间划分为第二指定数量的等份；
    对于所述成员小区中的每一个预设权值，分别确定所述每一个预设权值所对应的每一个所述服务小区参考信号接收功率落入每个所述等份的频率，确定在频率累计分布为第二指定频率的情况下所对应的最大参考信号接收功率；
    对于每一个成员小区，按数值从高到低对所述成员小区所对应的多个所述最大参考信号接收功率排序，将排序靠前的一个或多个所述最大参考信号接收功率所对应的一个或多个预设权值作为所述成员小区的所述成员备选广播波束权值。
  5. 根据权利要求4所述的方法，其中，对于所述成员小区所对应的预设权值中所包括的第一预设权值和第二预设权值，所述第二预设权值所对应的第一终端的服务小区参考信号接收功率为所述第一预设权值所对应的所述第一终端的服务小区参考信号接收功率与第一天线增益之和，其中，所述第一预设权值所对应的所述第一终端的所述服务小区参考信号接收功率是测量得到的，所述第一天线增益是根据所述第二预设权值、所述第一预设权值和所述第一终端的波达方向所确定的。
  6. 根据权利要求2所述的方法，其中，所述根据所述第一子网所包括的每一个所述成员小区内的终端在成员备选广播波束权值条件下的信号与干扰加噪声比从每一个所述成员小区的所述成员备选广播波束权值中确定所述子网目标广播波束权值集合，包括：
    对于所述第一子网，利用蚁群算法从每一个所述成员小区的所述成员备选广播波束权值中确定所述第一子网的所述子网目标广播波束权值集合，其中，所述蚁群算法的解为所述子网目标广播波束权值集合，每一轮迭代过程中包括了多只蚂蚁，每只蚂蚁的选择结果为一个子网广播波束权值集合，所述子网广播波束权值集合中包括了蚂蚁从每个成员小区的所述成员备选广播波束权值中所选择的广播波束权值。
  7. 根据权利要求6所述的方法，其中，所述利用蚁群算法从每一个所述成员小区的所述成员备选广播波束权值中确定所述第一子网的所述子网目标广播 波束权值集合，包括：
    每只蚂蚁选择所述成员备选广播波束权值的概率与所述成员备选广播波束权值的期望值呈正相关的关系，所述成员备选广播波束权值的期望值与上一轮迭代过程中，选择了所述成员备选广播波束权值的蚂蚁所对应的子网广播波束权值集合的子网信号与干扰加噪声比呈正相关的关系，所述第一子网的子网信号与干扰加噪声比是利用函数处理所述第一子网的子网广播波束权值集合条件下的成员小区内的终端的信号与干扰加噪声比所得到的。
  8. 根据权利要求7所述的方法，其中，在每一轮迭代过程中，每个成员备选广播波束权值的期望值为：上一轮迭代过程中，所有选择了所述成员备选广播波束权值的蚂蚁所对应的子网广播波束权值集合的子网信号与干扰加噪声比的平均值。
  9. 根据权利要求7所述的方法，其中，所述第一子网的子网信号与干扰加噪声比是利用函数处理所述第一子网的子网广播波束权值集合条件下的成员小区内的终端的信号与干扰加噪声比所得到的，包括：
    对于所述第一子网，在每一轮迭代过程开始之前，对于在上一轮迭代过程中的每一个蚂蚁，确定每一个所述蚂蚁所选择的子网广播波束权值集合条件下的终端的信号与干扰加噪声比；
    将所述第一子网的所有所述终端的信号与干扰加噪声比所组成的区间划分为第三指定数量的等份；
    对于所述第一子网，分别确定所述第一子网的所有终端的信号与干扰加噪声比落入每个所述等份的频率，确定在频率累计分布为第三指定频率的情况下所对应的最大信号与干扰加噪声比，将所述最大信号与干扰加噪声比作为所述子网广播波束权值集合所对应的子网信号与干扰加噪声比。
  10. 根据权利要求7所述的方法，其中，所述成员小区内的终端的信号与干扰加噪声比为：所述终端所在的服务小区的参考信号接收功率，与，所述终端所测量得到的所述服务小区的邻区的邻区参考信号接收功率之和加白噪声功率，的比。
  11. 根据权利要求10所述的方法，其中，对于所述成员小区所对应的成员备选广播波束权值中所包括的第一成员备选广播波束权值和第二成员备选广 播波束权值，所述第一成员备选广播波束权值所对应的第一终端的所述邻区参考信号接收功率为所述第二成员备选广播波束权值所对应的所述第一终端的所述邻区参考信号接收功率与第二天线增益之和，其中，所述第二成员备选广播波束权值所对应的所述第一终端的所述邻区参考信号接收功率是所述第一终端测量得到的，所述第二天线增益是根据所述第一成员备选广播波束权值、所述第二成员备选广播波束权值和所述第一终端的波达方向所确定的。
  12. 根据权利要求6所述的方法，其中，所述利用蚁群算法从每一个所述成员小区的所述成员备选广播波束权值中确定所述第一子网的所述子网目标广播波束权值集合，还包括：
    在一轮迭代过程开始之前，更新每个成员小区中的每个成员备选广播波束权值的信息素浓度，其中，所述成员备选广播波束权值被蚂蚁选择的概率与所述成员备选广播波束权值的所述信息素浓度呈正相关的关系，所述信息素的浓度与所述成员备选广播波束权值在上一轮迭代过程中被蚂蚁选择的次数呈正相关的关系。
  13. 根据权利要求6所述的方法，其中，所述利用蚁群算法从每一个所述成员小区的所述成员备选广播波束权值中确定所述第一子网的所述子网目标广播波束权值集合，还包括：
    达到预设的迭代次数之后，将多个所述子网广播波束权值集合中，最大的子网信号与干扰加噪声比所对应的子网广播波束权值集合作为所述子网目标广播波束权值集合。
  14. 根据权利要求1所述的方法，其中，第一小区与第二小区的小区间重叠覆盖程度为第一重叠覆盖度与第二重叠覆盖度的平均值，其中，所述第一重叠覆盖度为所述第一小区相对于所述第二小区的重叠覆盖度，所述第二重叠覆盖度为所述第二小区相对于所述第一小区的重叠覆盖度。
  15. 根据权利要求14所述的方法，其中，所述第一重叠覆盖度为：满足第一条件的测量报告样本数与所述第一小区中满足第二条件的测量报告样本数的比值，其中，所述第一条件包括：所述第一小区的参考信号接收功率大于或等于第一阈值，并且，所述第二小区的参考信号接收功率大于或等于第二阈值，并且，所述第二小区的参考信号接收功率与所述第一小区的参考信号接收功率 的差值的绝对值大于或等于第三阈值，所述第二条件包括：所述第一小区的参考信号接收功率大于或等于所述第一阈值；或者，
    所述第二重叠覆盖度为：满足第三条件的测量报告样本数与所述第二小区中满足第四条件的测量报告样本数的比值，其中，所述第三条件包括：所述第二小区的参考信号接收功率大于或等于第四阈值，并且，所述第一小区的参考信号接收功率大于或等于第五阈值，并且，所述第一小区的参考信号接收功率与所述第二小区的参考信号接收功率的差值的绝对值大于或等于第六阈值，所述第四条件包括：所述第二小区的参考信号接收功率大于或等于所述第四阈值。
  16. 根据权利要求1所述的方法，其中，在所述将确定后的所述子网目标广播波束权值集合发送至所述第一子网之后，所述方法还包括：
    按照预设指标对所述子网目标广播波束权值集合进行评估，在评估结果不满足所述预设指标的情况下，回退所述子网目标广播波束权值集合为初始权值集合；
    在所述评估结果满足所述预设指标的情况下，按照发送至所述第一子网的所述子网目标广播波束权值集合发送广播波束。
  17. 根据权利要求16所述的方法，其中，所述预设指标包括以下至少之一：
    无线资源控制连接建立成功率指标、系统内切换出成功率指标、无线掉线率指标、频谱效率指标、平均激活用户数指标。
  18. 根据权利要求1至17中任一项所述的方法，还包括：
    根据确定的所述成员目标广播波束权值调整对应成员小区的成员业务波束权值，得到成员目标业务波束权值，其中，所述成员目标业务波束权值用于指示对应的目标小区根据所述成员目标业务波束权值发送业务波束。
  19. 根据权利要求18所述的方法，其中，所述根据确定的所述成员目标广播波束权值调整对应成员小区的成员业务波束权值，得到成员目标业务波束权值，包括以下至少之一：
    将所述成员目标广播波束权值的方位角作为所述成员业务波束权值的方位角，得到所述成员目标业务波束权值；
    将所述成员目标业务波束权值的下倾角范围覆盖所述成员广播波束权值的下倾角，得到所述成员目标业务波束权值。
  20. 根据权利要求19所述的方法，其中，按照预设的波束数量和预设的波束下倾角间距确定所述成员目标业务波束权值的下倾角。
  21. 一种权值的发送装置，包括：
    分割模块，设置为分割多个小区，得到一个或多个子网，其中，所述子网包括一个或多个所述小区，对于所述子网所包括的任意一个第一成员小区，所述第一成员小区与所述第一成员小区所在的子网中的第二成员小区的小区间重叠覆盖程度高于预设的程度阈值，所述第二成员小区为所述第一成员小区的邻小区；
    确定模块，设置为对于所述一个或多个子网中的任意一个第一子网，根据以下至少之一在成员小区的预设权值中确定所述第一子网的子网目标广播波束权值集合：所述第一子网所包括的成员小区的小区覆盖、所述第一子网所包括的成员小区的小区间干扰，其中，所述子网目标广播波束权值集合包括所述第一子网中的每一个所述成员小区的成员目标广播波束权值；
    发送模块，设置为将确定后的所述子网目标广播波束权值集合发送至所述第一子网，其中，所述子网目标广播波束权值集合用于指示所述第一子网中的成员小区根据所述子网目标广播波束权值集合中对应的所述成员目标广播波束权值发送广播波束。
  22. 一种计算机可读的存储介质，所述存储介质中存储有计算机程序，其中，所述计算机程序被设置为运行时执行所述权利要求1至20中任一项所述的权值的发送方法。
  23. 一种电子装置，包括存储器和处理器，所述存储器中存储有计算机程序，所述处理器被设置为运行所述计算机程序以执行所述权利要求1至20中任一项所述的权值的发送方法。
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